diff --git a/machine-learning/notebooks/python/OfficeHours_OML_Datastore_for_R_and_Python.json b/machine-learning/notebooks/python/OfficeHours_OML_Datastore_for_R_and_Python.json new file mode 100644 index 00000000..b52cc28f --- /dev/null +++ b/machine-learning/notebooks/python/OfficeHours_OML_Datastore_for_R_and_Python.json @@ -0,0 +1,2021 @@ +{ + "paragraphs": [ + { + "text": "%md\n# Oracle Machine Learning Datastore in Autonomous Database\n\nOracle Machine Learning provides datastores to save your native R or Python objects such as ML models and lists, as well as OML4R or OML4Py proxy objects in your Oracle Database or Autonomous Database instance for use in embedded execution and access across database sessions.\n\n---\n\nCopyright (c) 2022 Oracle Corporation \n###### The Universal Permissive License (UPL), Version 1.0\n\n---\n\n## Initialize interpreters for R and Python and create native model objects\n", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:08:35+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "

Oracle Machine Learning Datastore in Autonomous Database

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Oracle Machine Learning provides datastores to save your native R or Python objects such as ML models and lists, as well as OML4R or OML4Py proxy objects in your Oracle Database or Autonomous Database instance for use in embedded execution and access across database sessions.

\n
\n

Copyright (c) 2022 Oracle Corporation

\n
The Universal Permissive License (UPL), Version 1.0
\n
\n

Initialize interpreters for R and Python and create native model objects

\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-1957419806", + "id": "20221011-180410_326909485", + "dateCreated": "2022-10-07T19:33:33+0000", + "dateStarted": "2022-10-11T18:08:35+0000", + "dateFinished": "2022-10-11T18:08:36+0000", + "status": "FINISHED", + "focus": true, + "$$hashKey": "object:41" + }, + { + "title": "Import OML4R 'ORE' package and create an in-database machine learning model", + "text": "%r\n\nlibrary(ORE) \nore.sync(table = 'IRIS_R') \n\nglm.mod <- ore.odmGLM(Petal.Length~., IRIS_R) \nsummary(glm.mod)\n\n", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:08:36+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "graph": { + "mode": "table", + "height": 300, + "optionOpen": false, + "keys": [], + "values": [], + "groups": [], + "scatter": {} + }, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TEXT", + "data": "\nCall:\nore.odmGLM(formula = Petal.Length ~ ., data = IRIS_R)\n\nResiduals:\n Min 1Q Median 3Q Max \n-0.78396 -0.15708 0.00193 0.14730 0.65418 \n\nCoefficients:\n Estimate Std. Error t value Pr(>|t|) \n(Intercept) -1.11099 0.26987 -4.117 6.45e-05 ***\nSepal.Length 0.60801 0.05024 12.101 < 2e-16 ***\nSepal.Width -0.18052 0.08036 -2.246 0.0262 * \nPetal.Width 0.60222 0.12144 4.959 1.97e-06 ***\nSpeciesversicolor 1.46337 0.17345 8.437 3.14e-14 ***\nSpeciesvirginica 1.97422 0.24480 8.065 2.60e-13 ***\n---\nSignif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n\nResidual standard error: 0.2627 on 144 degrees of freedom\nMultiple R-squared: 0.9786,\tAdjusted R-squared: 0.9778 \nF-statistic: 1317 on 5 and 144 DF, p-value: < 2.2e-16\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_800081049", + "id": "20221011-180410_347481396", + "dateCreated": "2022-10-03T02:53:48+0000", + "dateStarted": "2022-10-11T18:08:37+0000", + "dateFinished": "2022-10-11T18:08:55+0000", + "status": "FINISHED", + "$$hashKey": "object:42" + }, + { + "title": "Import OML4Py 'oml' package and create an in-database machine learning model", + "text": "%python\n\nimport oml\n\nIRIS_PY = oml.sync(table = \"IRIS_PY\")\n\ntrain_x = IRIS_PY.drop('PETAL_LENGTH')\ntrain_y = IRIS_PY['PETAL_LENGTH']\n\nglm_mod = oml.glm(\"regression\")\nglm_mod = glm_mod.fit(train_x, train_y)\nglm_mod", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:08:55+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TEXT", + "data": "\nAlgorithm Name: Generalized Linear Model\n\nMining Function: REGRESSION\n\nTarget: PETAL_LENGTH\n\nSettings: \n setting name setting value\n0 ALGO_NAME ALGO_GENERALIZED_LINEAR_MODEL\n1 GLMS_CONF_LEVEL .95\n2 GLMS_FTR_GENERATION GLMS_FTR_GENERATION_DISABLE\n3 GLMS_FTR_SELECTION GLMS_FTR_SELECTION_DISABLE\n4 ODMS_DETAILS ODMS_ENABLE\n5 ODMS_MISSING_VALUE_TREATMENT ODMS_MISSING_VALUE_AUTO\n6 ODMS_SAMPLING ODMS_SAMPLING_DISABLE\n7 PREP_AUTO ON\n\nComputed Settings: \n setting name setting value\n0 GLMS_CONV_TOLERANCE .0000050000000000000004\n1 GLMS_NUM_ITERATIONS 30\n2 GLMS_RIDGE_REGRESSION GLMS_RIDGE_REG_DISABLE\n3 GLMS_SOLVER GLMS_SOLVER_CHOL\n\nGlobal Statistics: \n attribute name attribute value\n0 ADJUSTED_R_SQUARE 0.97785\n1 AIC -395.115\n2 COEFF_VAR 6.99114\n3 CONVERGED YES\n4 CORRECTED_TOTAL_DF 149\n5 CORRECTED_TOT_SS 464.325\n6 DEPENDENT_MEAN 3.758\n7 ERROR_DF 144\n8 ERROR_MEAN_SQUARE 0.0690256\n9 ERROR_SUM_SQUARES 9.93968\n10 F_VALUE 1316.57\n11 GMSEP 0.0719153\n12 HOCKING_SP 0.000482696\n13 J_P 0.0717866\n14 MODEL_DF 5\n15 MODEL_F_P_VALUE 0\n16 MODEL_MEAN_SQUARE 90.8771\n17 MODEL_SUM_SQUARES 454.386\n18 NUM_PARAMS 6\n19 NUM_ROWS 150\n20 RANK_DEFICIENCY 0\n21 ROOT_MEAN_SQ 0.262727\n22 R_SQ 0.978593\n23 SBIC -377.051\n24 VALID_COVARIANCE_MATRIX YES\n\nAttributes: \nPETAL_WIDTH\nSEPAL_LENGTH\nSEPAL_WIDTH\nSPECIES\n\nPartition: NO\n\nCoefficients: \n\n attribute name attribute value ... p value significance code\n0 (Intercept) None ... 6.445916e-05 ***\n1 PETAL_WIDTH None ... 1.968679e-06 ***\n2 SEPAL_LENGTH None ... 1.073592e-23 ***\n3 SEPAL_WIDTH None ... 2.619373e-02 *\n4 SPECIES versicolor ... 3.142686e-14 ***\n5 SPECIES virginica ... 2.600021e-13 ***\n\n[6 rows x 7 columns]\n\nSignif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 '\n\nFit Details: \n\n name value\n0 ADJUSTED_R_SQUARE 9.778500e-01\n1 AIC -3.951150e+02\n2 COEFF_VAR 6.991144e+00\n3 CORRECTED_TOTAL_DF 1.490000e+02\n4 CORRECTED_TOT_SS 4.643254e+02\n5 DEPENDENT_MEAN 3.758000e+00\n6 ERROR_DF 1.440000e+02\n7 ERROR_MEAN_SQUARE 6.902558e-02\n8 ERROR_SUM_SQUARES 9.939683e+00\n9 F_VALUE 1.316572e+03\n10 GMSEP 7.191532e-02\n11 HOCKING_SP 4.826963e-04\n12 J_P 7.178660e-02\n13 MODEL_CONVERGED 1.000000e+00\n14 MODEL_DF 5.000000e+00\n15 MODEL_F_P_VALUE 2.879219e-118\n16 MODEL_MEAN_SQUARE 9.087714e+01\n17 MODEL_SUM_SQUARES 4.543857e+02\n18 NUM_PARAMS 6.000000e+00\n19 NUM_ROWS 1.500000e+02\n20 RANK_DEFICIENCY 0.000000e+00\n21 ROOT_MEAN_SQ 2.627272e-01\n22 R_SQ 9.785933e-01\n23 SBIC -3.770512e+02\n24 VALID_COVARIANCE_MATRIX 1.000000e+00\n\nRank: \n\n6\n\nDeviance: \n\n9.939683\n\nAIC: \n\n-395\n\nNull Deviance: \n\n464.3254\n\nDF Residual: \n\n144.0\n\nDF Null: \n\n149.0\n\nConverged: \n\nTrue\n\n\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_373381864", + "id": "20221011-180410_689531645", + "dateCreated": "2022-10-03T02:54:12+0000", + "dateStarted": "2022-10-11T18:08:56+0000", + "dateFinished": "2022-10-11T18:09:01+0000", + "status": "FINISHED", + "$$hashKey": "object:43" + }, + { + "text": "%md\n---", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:01+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "
\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-1754821012", + "id": "20221011-180410_1365052265", + "dateCreated": "2022-10-10T21:15:31+0000", + "dateStarted": "2022-10-11T18:09:01+0000", + "dateFinished": "2022-10-11T18:09:01+0000", + "status": "FINISHED", + "$$hashKey": "object:44" + }, + { + "title": "Create a native R machine learning model", + "text": "%r\n\nlm.mod <- lm(Petal.Length~Petal.Width, family='binomial', iris) \nsummary(lm.mod)", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:01+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TEXT", + "data": "Warning message:\n“In lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) :\n extra argument ‘family’ will be disregarded”\n\nCall:\nlm(formula = Petal.Length ~ Petal.Width, data = iris, family = \"binomial\")\n\nResiduals:\n Min 1Q Median 3Q Max \n-1.33542 -0.30347 -0.02955 0.25776 1.39453 \n\nCoefficients:\n Estimate Std. Error t value Pr(>|t|) \n(Intercept) 1.08356 0.07297 14.85 <2e-16 ***\nPetal.Width 2.22994 0.05140 43.39 <2e-16 ***\n---\nSignif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n\nResidual standard error: 0.4782 on 148 degrees of freedom\nMultiple R-squared: 0.9271,\tAdjusted R-squared: 0.9266 \nF-statistic: 1882 on 1 and 148 DF, p-value: < 2.2e-16\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_711262739", + "id": "20221011-180410_597875257", + "dateCreated": "2022-10-10T21:15:13+0000", + "dateStarted": "2022-10-11T18:09:01+0000", + "dateFinished": "2022-10-11T18:09:01+0000", + "status": "FINISHED", + "$$hashKey": "object:45" + }, + { + "title": "Create a native Python machine learning model", + "text": "%python\n\nfrom sklearn import linear_model\n\niris = IRIS_PY.pull()\n\nX = iris[['PETAL_WIDTH']]\ny = iris[['PETAL_LENGTH']]\n\nlm = linear_model.LinearRegression()\n\nlm_mod = lm.fit(X, y)\n\nprint(lm_mod.intercept_, lm_mod.coef_, lm_mod.score(X, y))\n", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:01+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TEXT", + "data": "[1.08355803] [[2.2299405]] 0.9271098389904927\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1236589925", + "id": "20221011-180410_110675196", + "dateCreated": "2022-10-10T21:20:24+0000", + "dateStarted": "2022-10-11T18:09:02+0000", + "dateFinished": "2022-10-11T18:09:02+0000", + "status": "FINISHED", + "$$hashKey": "object:46" + }, + { + "text": "%md\n\n## Save model objects in a datastore\n", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:02+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "

Save model objects in a datastore

\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-491186633", + "id": "20221011-180410_1681135696", + "dateCreated": "2022-10-07T19:33:11+0000", + "dateStarted": "2022-10-11T18:09:02+0000", + "dateFinished": "2022-10-11T18:09:02+0000", + "status": "FINISHED", + "$$hashKey": "object:47" + }, + { + "title": "Save Model and Objects into datastore in R", + "text": "%r\n\nore.save(glm.mod, lm.mod, name = \"ds-r-1\", overwrite = TRUE)\n\nlist <- list(a = 1, b = TRUE, c = \"hoopsa\")\n\nore.save(list, name = \"ds-r-1\", append = TRUE)", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:02+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1509679628", + "id": "20221011-180410_1569411580", + "dateCreated": "2022-10-03T02:54:21+0000", + "dateStarted": "2022-10-11T18:09:02+0000", + "dateFinished": "2022-10-11T18:09:05+0000", + "status": "FINISHED", + "$$hashKey": "object:48" + }, + { + "title": "Save Model and Objects into datastore in Python", + "text": "%python\n\noml.ds.save(objs={'glm_mod': glm_mod, 'lm_mod': lm_mod}, name=\"ds-py-1\", overwrite=True)\n\ndict ={'a':1, 'b': True, 'c': \"hoopsa\"}\n\noml.ds.save(objs={'list': dict}, name=\"ds-py-1\", append=True)", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:05+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1135521586", + "id": "20221011-180410_1758276454", + "dateCreated": "2022-10-03T02:54:36+0000", + "dateStarted": "2022-10-11T18:09:05+0000", + "dateFinished": "2022-10-11T18:09:08+0000", + "status": "FINISHED", + "$$hashKey": "object:49" + }, + { + "text": "%md\n\n## List and view contents of datastores", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:08+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "

List and view contents of datastores

\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-2048060312", + "id": "20221011-180410_674409895", + "dateCreated": "2022-10-07T19:35:27+0000", + "dateStarted": "2022-10-11T18:09:08+0000", + "dateFinished": "2022-10-11T18:09:08+0000", + "status": "FINISHED", + "$$hashKey": "object:50" + }, + { + "title": "List datastore details using R", + "text": "%r\n\nore.datastore(\"ds-r-1\")", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:08+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "\n\n\n\t\n\t\n\n\n\t\n\n
A data.frame: 1 x 5
datastore.nameobject.countsizecreation.datedescription
<chr><dbl><dbl><dttm><chr>
ds-r-13291682022-10-11 18:09:02NA
\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_216894037", + "id": "20221011-180410_1811994217", + "dateCreated": "2022-10-03T02:57:22+0000", + "dateStarted": "2022-10-11T18:09:08+0000", + "dateFinished": "2022-10-11T18:09:08+0000", + "status": "FINISHED", + "$$hashKey": "object:51" + }, + { + "title": "List datastore details using Python", + "text": "%python\n\noml.ds.dir(name=\"ds-py-1\")", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:08+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": { + "0": { + "graph": { + "mode": "table", + "height": 134.534, + "optionOpen": false + } + } + }, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TEXT", + "data": " datastore_name object_count size date description\n0 ds-py-1 3 4367 2022-10-11 18:09:05 None\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1020999520", + "id": "20221011-180410_1803775652", + "dateCreated": "2022-10-03T02:58:04+0000", + "dateStarted": "2022-10-11T18:09:08+0000", + "dateFinished": "2022-10-11T18:09:08+0000", + "status": "FINISHED", + "$$hashKey": "object:52" + }, + { + "text": "%md\n---\n", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:08+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "
\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_874032002", + "id": "20221011-180410_1788149417", + "dateCreated": "2022-10-07T19:36:28+0000", + "dateStarted": "2022-10-11T18:09:09+0000", + "dateFinished": "2022-10-11T18:09:09+0000", + "status": "FINISHED", + "$$hashKey": "object:53" + }, + { + "title": "View datastore contents using R", + "text": "%r\n\nore.datastoreSummary(\"ds-r-1\")", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:09+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "\n\n\n\t\n\t\n\n\n\t\n\t\n\t\n\n
A data.frame: 3 x 6
object.nameclasssizelengthrow.countcol.count
<chr><chr><dbl><dbl><dbl><dbl>
glm.modore.odmGLM1237726NANA
list list 132 3NANA
lm.mod lm 1665912NANA
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Load datastore objects into memory

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Error t value Pr(>|t|) \n(Intercept) -1.11099 0.26987 -4.117 6.45e-05 ***\nSepal.Length 0.60801 0.05024 12.101 < 2e-16 ***\nSepal.Width -0.18052 0.08036 -2.246 0.0262 * \nPetal.Width 0.60222 0.12144 4.959 1.97e-06 ***\nSpeciesversicolor 1.46337 0.17345 8.437 3.14e-14 ***\nSpeciesvirginica 1.97422 0.24480 8.065 2.60e-13 ***\n---\nSignif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n\nResidual standard error: 0.2627 on 144 degrees of freedom\nMultiple R-squared: 0.9786,\tAdjusted R-squared: 0.9778 \nF-statistic: 1317 on 5 and 144 DF, p-value: < 2.2e-16\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-1230574619", + "id": "20221011-180410_726801076", + "dateCreated": "2022-10-10T21:33:43+0000", + "dateStarted": "2022-10-11T18:09:20+0000", + "dateFinished": "2022-10-11T18:09:20+0000", + "status": "FINISHED", + "$$hashKey": "object:63" + }, + { + "title": "Summarize loaded OML4Py model", + "text": "%python\n\nglm_mod", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:20+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "editorHide": false, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TEXT", + "data": "\nAlgorithm Name: Generalized Linear Model\n\nMining Function: REGRESSION\n\nTarget: PETAL_LENGTH\n\nSettings: \n setting name setting value\n0 ALGO_NAME ALGO_GENERALIZED_LINEAR_MODEL\n1 GLMS_CONF_LEVEL .95\n2 GLMS_FTR_GENERATION GLMS_FTR_GENERATION_DISABLE\n3 GLMS_FTR_SELECTION GLMS_FTR_SELECTION_DISABLE\n4 ODMS_DETAILS ODMS_ENABLE\n5 ODMS_MISSING_VALUE_TREATMENT ODMS_MISSING_VALUE_AUTO\n6 ODMS_SAMPLING ODMS_SAMPLING_DISABLE\n7 PREP_AUTO ON\n\nComputed Settings: \n setting name setting value\n0 GLMS_CONV_TOLERANCE .0000050000000000000004\n1 GLMS_NUM_ITERATIONS 30\n2 GLMS_RIDGE_REGRESSION GLMS_RIDGE_REG_DISABLE\n3 GLMS_SOLVER GLMS_SOLVER_CHOL\n\nGlobal Statistics: \n attribute name attribute value\n0 ADJUSTED_R_SQUARE 0.97785\n1 AIC -395.115\n2 COEFF_VAR 6.99114\n3 CONVERGED YES\n4 CORRECTED_TOTAL_DF 149\n5 CORRECTED_TOT_SS 464.325\n6 DEPENDENT_MEAN 3.758\n7 ERROR_DF 144\n8 ERROR_MEAN_SQUARE 0.0690256\n9 ERROR_SUM_SQUARES 9.93968\n10 F_VALUE 1316.57\n11 GMSEP 0.0719153\n12 HOCKING_SP 0.000482696\n13 J_P 0.0717866\n14 MODEL_DF 5\n15 MODEL_F_P_VALUE 0\n16 MODEL_MEAN_SQUARE 90.8771\n17 MODEL_SUM_SQUARES 454.386\n18 NUM_PARAMS 6\n19 NUM_ROWS 150\n20 RANK_DEFICIENCY 0\n21 ROOT_MEAN_SQ 0.262727\n22 R_SQ 0.978593\n23 SBIC -377.051\n24 VALID_COVARIANCE_MATRIX YES\n\nAttributes: \nPETAL_WIDTH\nSEPAL_LENGTH\nSEPAL_WIDTH\nSPECIES\n\nPartition: NO\n\nCoefficients: \n\n attribute name attribute value ... p value significance code\n0 (Intercept) None ... 6.445916e-05 ***\n1 PETAL_WIDTH None ... 1.968679e-06 ***\n2 SEPAL_LENGTH None ... 1.073592e-23 ***\n3 SEPAL_WIDTH None ... 2.619373e-02 *\n4 SPECIES versicolor ... 3.142686e-14 ***\n5 SPECIES virginica ... 2.600021e-13 ***\n\n[6 rows x 7 columns]\n\nSignif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 '\n\nFit Details: \n\n name value\n0 ADJUSTED_R_SQUARE 9.778500e-01\n1 AIC -3.951150e+02\n2 COEFF_VAR 6.991144e+00\n3 CORRECTED_TOTAL_DF 1.490000e+02\n4 CORRECTED_TOT_SS 4.643254e+02\n5 DEPENDENT_MEAN 3.758000e+00\n6 ERROR_DF 1.440000e+02\n7 ERROR_MEAN_SQUARE 6.902558e-02\n8 ERROR_SUM_SQUARES 9.939683e+00\n9 F_VALUE 1.316572e+03\n10 GMSEP 7.191532e-02\n11 HOCKING_SP 4.826963e-04\n12 J_P 7.178660e-02\n13 MODEL_CONVERGED 1.000000e+00\n14 MODEL_DF 5.000000e+00\n15 MODEL_F_P_VALUE 2.879219e-118\n16 MODEL_MEAN_SQUARE 9.087714e+01\n17 MODEL_SUM_SQUARES 4.543857e+02\n18 NUM_PARAMS 6.000000e+00\n19 NUM_ROWS 1.500000e+02\n20 RANK_DEFICIENCY 0.000000e+00\n21 ROOT_MEAN_SQ 2.627272e-01\n22 R_SQ 9.785933e-01\n23 SBIC -3.770512e+02\n24 VALID_COVARIANCE_MATRIX 1.000000e+00\n\nRank: \n\n6\n\nDeviance: \n\n9.939683\n\nAIC: \n\n-395\n\nNull Deviance: \n\n464.3254\n\nDF Residual: \n\n144.0\n\nDF Null: \n\n149.0\n\nConverged: \n\nTrue\n\n\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-1997999501", + "id": "20221011-180410_414115165", + "dateCreated": "2022-10-10T21:34:38+0000", + "dateStarted": "2022-10-11T18:09:21+0000", + "dateFinished": "2022-10-11T18:09:21+0000", + "status": "FINISHED", + "$$hashKey": "object:64" + }, + { + "text": "%md\n\n## Delete datastores and datastore contents", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:21+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + 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Delete datastores and datastore contents

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A data.frame: 2 x 6
object.nameclasssizelengthrow.countcol.count
<chr><chr><dbl><dbl><dbl><dbl>
list list 132 3NANA
lm.modlm 1665912NANA
\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_468840831", + "id": "20221011-180410_282624497", + "dateCreated": "2022-10-10T21:36:11+0000", + "dateStarted": "2022-10-11T18:09:24+0000", + "dateFinished": "2022-10-11T18:09:25+0000", + "status": "FINISHED", + "$$hashKey": "object:69" + }, + { + "title": "View updated datastore contents using Python", + "text": "%python\n\noml.ds.describe(name = \"ds-py-1\")", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:25+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "text", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "editorHide": false, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TEXT", + "data": " object_name class size length row_count col_count\n0 list dict 40 3 1 3\n1 lm_mod LinearRegression 604 1 1 1\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_771763831", + "id": "20221011-180410_63988665", + "dateCreated": "2022-10-10T21:36:54+0000", + "dateStarted": "2022-10-11T18:09:25+0000", + "dateFinished": "2022-10-11T18:09:25+0000", + "status": "FINISHED", + "$$hashKey": "object:70" + }, + { + "text": "%md\n---", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:25+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": false, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "
\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-630137495", + "id": "20221011-180410_1249180895", + "dateCreated": "2022-10-10T21:36:08+0000", + "dateStarted": "2022-10-11T18:09:26+0000", + "dateFinished": "2022-10-11T18:09:26+0000", + "status": "FINISHED", + "$$hashKey": "object:71" + }, + { + "title": "Delete datastore in R", + "text": "%r\n\nore.delete('ds-r-1')", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:26+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "'ds-r-1'" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-566581153", + "id": "20221011-180410_811315216", + "dateCreated": "2022-10-03T03:00:31+0000", + "dateStarted": "2022-10-11T18:09:26+0000", + "dateFinished": "2022-10-11T18:09:26+0000", + "status": "FINISHED", + "$$hashKey": "object:72" + }, + { + "title": "Delete datastore in Python", + "text": "%python\n\noml.ds.delete(name='ds-py-1')", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:26+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TEXT", + "data": "'ds-py-1'\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-1759378045", + "id": "20221011-180410_1691904227", + "dateCreated": "2022-10-03T03:01:02+0000", + "dateStarted": "2022-10-11T18:09:26+0000", + "dateFinished": "2022-10-11T18:09:26+0000", + "status": "FINISHED", + "$$hashKey": "object:73" + }, + { + "text": "%md\n---", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:26+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "
\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_45582957", + "id": "20221011-180410_1679098474", + "dateCreated": "2022-10-07T19:51:29+0000", + "dateStarted": "2022-10-11T18:09:27+0000", + "dateFinished": "2022-10-11T18:09:27+0000", + "status": "FINISHED", + "$$hashKey": "object:74" + }, + { + "title": "Create new datastore for next example", + "text": "%r\n\nore.save(glm.mod, \n name = \"ds-r-2\", \n overwrite = TRUE)\n", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:27+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1371390703", + "id": "20221011-180410_157980723", + "dateCreated": "2022-10-07T19:51:45+0000", + "dateStarted": "2022-10-11T18:09:27+0000", + "dateFinished": "2022-10-11T18:09:27+0000", + "status": "FINISHED", + "$$hashKey": "object:75" + }, + { + "title": "Create new datastore for next example", + "text": "%python\n\noml.ds.save(objs={'glm_mod': glm_mod}, \n name=\"ds-py-2\", \n grantable = True, \n overwrite=True)\n\n", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:27+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "editorHide": false, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_2112018123", + "id": "20221011-180410_1683776062", + "dateCreated": "2022-10-07T19:51:59+0000", + "dateStarted": "2022-10-11T18:09:27+0000", + "dateFinished": "2022-10-11T18:09:27+0000", + "status": "FINISHED", + "$$hashKey": "object:76" + }, + { + "text": "%md\n---", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:27+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/osql", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "
\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1961328874", + "id": "20221011-180410_1130660134", + "dateCreated": "2022-10-07T19:52:02+0000", + "dateStarted": "2022-10-11T18:09:28+0000", + "dateFinished": "2022-10-11T18:09:28+0000", + "status": "FINISHED", + "$$hashKey": "object:77" + }, + { + "title": "Delete datastore in R using SQL", + "text": "%script\n\nBEGIN \n rqDropDataStore('ds-r-2'); \nEND; \n/", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:28+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "plsql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/plsql", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TEXT", + "data": "\nPL/SQL procedure successfully completed.\n\n\n---------------------------\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-1502377923", + "id": "20221011-180410_263114098", + "dateCreated": "2022-10-03T03:01:18+0000", + "dateStarted": "2022-10-11T18:09:28+0000", + "dateFinished": "2022-10-11T18:09:28+0000", + "status": "FINISHED", + "$$hashKey": "object:78" + }, + { + "title": "Delete datastore in Python using SQL", + "text": "%script\n\nBEGIN \n pyqDropDataStore('ds-py-2');\nEND;\n/", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:28+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "plsql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/plsql", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TEXT", + "data": "\nPL/SQL procedure successfully completed.\n\n\n---------------------------\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-992545126", + "id": "20221011-180410_1389914036", + "dateCreated": "2022-10-03T03:01:50+0000", + "dateStarted": "2022-10-11T18:09:29+0000", + "dateFinished": "2022-10-11T18:09:29+0000", + "status": "FINISHED", + "$$hashKey": "object:79" + }, + { + "text": "%md\n\n## Grant and revoke access privileges on datastores", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:29+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "

Grant and revoke access privileges on datastores

\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_379100453", + "id": "20221011-180410_1427284547", + "dateCreated": "2022-10-07T19:39:23+0000", + "dateStarted": "2022-10-11T18:09:29+0000", + "dateFinished": "2022-10-11T18:09:29+0000", + "status": "FINISHED", + "$$hashKey": "object:80" + }, + { + "title": "Grant datastore access to a user in R", + "text": "%r\n\nore.save(glm.mod, \n name = 'ds-r-glm-mod', \n grantable = TRUE, \n overwrite = TRUE)\n\nore.grant('ds-r-glm-mod', type = 'datastore', user = 'OMLUSER2')", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:29+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-317606835", + "id": "20221011-180410_848852086", + "dateCreated": "2022-10-03T03:02:03+0000", + "dateStarted": "2022-10-11T18:09:29+0000", + "dateFinished": "2022-10-11T18:09:29+0000", + "status": "FINISHED", + "$$hashKey": "object:81" + }, + { + "title": "Grant datastore access to a user in Python", + "text": "%python\n\noml.ds.save(objs={'glm_mod': glm_mod}, \n name= 'ds-py-glm-mod', \n grantable = True, \n overwrite = True)\n\noml.grant(name='ds-py-glm-mod', typ='datastore', user='OMLUSER2')", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:30+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1713023437", + "id": "20221011-180410_1260714506", + "dateCreated": "2022-10-03T03:02:14+0000", + "dateStarted": "2022-10-11T18:09:30+0000", + "dateFinished": "2022-10-11T18:09:31+0000", + "status": "FINISHED", + "$$hashKey": "object:82" + }, + { + "text": "%md\n---", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:31+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "
\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1302635853", + "id": "20221011-180410_1523630365", + "dateCreated": "2022-10-07T19:40:38+0000", + "dateStarted": "2022-10-11T18:09:31+0000", + "dateFinished": "2022-10-11T18:09:31+0000", + "status": "FINISHED", + "$$hashKey": "object:83" + }, + { + "title": "Revoke datastore access to a user in R", + "text": "%r\n\nore.revoke('ds-r-glm-mod', type = 'datastore', user = 'OMLUSER2')", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:31+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_195848255", + "id": "20221011-180410_437280958", + "dateCreated": "2022-10-03T03:02:24+0000", + "dateStarted": "2022-10-11T18:09:31+0000", + "dateFinished": "2022-10-11T18:09:31+0000", + "status": "FINISHED", + "$$hashKey": "object:84" + }, + { + "title": "Revoke datastore access to a user in Python", + "text": "%python\n\noml.revoke(name = 'ds-py-glm-mod', typ='datastore', user='OMLUSER2')", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:31+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1916066867", + "id": "20221011-180410_1801100366", + "dateCreated": "2022-10-03T03:02:33+0000", + "dateStarted": "2022-10-11T18:09:32+0000", + "dateFinished": "2022-10-11T18:09:32+0000", + "status": "FINISHED", + "$$hashKey": "object:85" + }, + { + "text": "%md\n\n# End of script\n", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:32+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "

End of script

\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-203265381", + "id": "20221011-180410_121819013", + "dateCreated": "2022-10-07T19:41:04+0000", + "dateStarted": "2022-10-11T18:09:32+0000", + "dateFinished": "2022-10-11T18:09:32+0000", + "status": "FINISHED", + "$$hashKey": "object:86" + } + ], + "name": "OML Datastore for R and Python", + "id": "124372", + "defaultInterpreterGroup": "spark", + "noteParams": {}, + "noteForms": {}, + "angularObjects": { + "ORA7A60DC9B32:OMLUSER-124372": [], + "MDW381939C745:shared_process": [] + }, + "config": { + "looknfeel": "default", + "personalizedMode": "false" + }, + "info": { + "isRunning": false + }, + "path": "/OML Datastore Notebook" +} \ No newline at end of file diff --git a/machine-learning/notebooks/r/OML4Py Feature Extraction ESA Wiki Model.json b/machine-learning/notebooks/r/OML4Py Feature Extraction ESA Wiki Model.json deleted file mode 100644 index 05021c73..00000000 --- a/machine-learning/notebooks/r/OML4Py Feature Extraction ESA Wiki Model.json +++ /dev/null @@ -1,1499 +0,0 @@ -{ - "paragraphs": [ - { - "text": "%md\n## Explicit Semantic Analysis (ESA) for Text Analytics\n\nExplicit Semantic Analysis (ESA) is an unsupervised algorithm for feature extraction of explicit features based on an existing knowledge base. It is the process of understanding the meaning of a section of text as a combination of the concepts found in the text. Compared to other techniques such as Latent Dirichlet Association (LDA) or Term Frequency-Inverse Document Frequency (TF-IDF), ESA offers some unique benefits. Most notably, it improves text document categorization by calculating `semantic relatedness` (how similar in meaning two words or pieces of text are to each other) between the documents and a set of topics that are explicitly defined and described by humans.\n\nThe Oracle Machine Learning for Python function *oml.esa* extracts text-based features from a corpus of documents and performs document similarity comparisons. All processing occurs inside Oracle Autonomous Database.\n\nIn this notebook, we'll use the Wikipedia Model as an example:\n\n - Create an OML4Py proxy ESA model object for the pre-loaded Wikipedia model\n - Examples of using the Wiki ESA model\n - Basic ESA Wiki model features for words\n - Basic ESA Wiki model features for phrases\n - ESA Wiki Model document similarity on phrases\n - ESA Wiki Model document similarity on long phrases\n \n*Note: The pre-built Wikipedia model must be installed in your Autonomous Database instance to run this notebook. See instructions below.*\n\nCopyright (c) 2022 Oracle Corporation \n###### The Universal Permissive License (UPL), Version 1.0\n---", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:54:10+0000", - "progress": 0, - "config": { - "tableHide": false, - "editorSetting": { - "language": "md", - "editOnDblClick": false, - "completionSupport": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Explicit Semantic Analysis (ESA) for Text Analytics

\n

Explicit Semantic Analysis (ESA) is an unsupervised algorithm for feature extraction of explicit features based on an existing knowledge base. It is the process of understanding the meaning of a section of text as a combination of the concepts found in the text. Compared to other techniques such as Latent Dirichlet Association (LDA) or Term Frequency-Inverse Document Frequency (TF-IDF), ESA offers some unique benefits. Most notably, it improves text document categorization by calculating semantic relatedness (how similar in meaning two words or pieces of text are to each other) between the documents and a set of topics that are explicitly defined and described by humans.

\n

The Oracle Machine Learning for Python function oml.esa extracts text-based features from a corpus of documents and performs document similarity comparisons. All processing occurs inside Oracle Autonomous Database.

\n

In this notebook, we'll use the Wikipedia Model as an example:

\n\n

Note: The pre-built Wikipedia model must be installed in your Autonomous Database instance to run this notebook. See instructions below.

\n

Copyright (c) 2022 Oracle Corporation

\n
The Universal Permissive License (UPL), Version 1.0
\n
\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_-1161149141", - "id": "20220729-215332_92019055", - "dateCreated": "2021-02-17T07:34:52+0000", - "dateStarted": "2022-07-29T21:54:10+0000", - "dateFinished": "2022-07-29T21:54:12+0000", - "status": "FINISHED", - "focus": true, - "$$hashKey": "object:40" - }, - { - "title": "For more information...", - "text": "%md\nOracle ADW Documentation https://docs.oracle.com/en/cloud/paas/autonomous-data-warehouse-cloud/index.html\nOML folder on Oracle Github : https://github.com/oracle/oracle-db-examples/tree/master/machine-learning\nOML web page: https://www.oracle.com/machine-learning\nOML Explicit Semantic Analysis: https://www.oracle.com/goto/ml-explicit-semantic-analysis", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:54:12+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Oracle ADW Documentation https://docs.oracle.com/en/cloud/paas/autonomous-data-warehouse-cloud/index.html\n
OML folder on Oracle Github : https://github.com/oracle/oracle-db-examples/tree/master/machine-learning\n
OML web page: https://www.oracle.com/machine-learning\n
OML Explicit Semantic Analysis: https://www.oracle.com/goto/ml-explicit-semantic-analysis

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_128804830", - "id": "20220729-215332_1417204985", - "dateCreated": "2021-07-20T18:14:43+0000", - "dateStarted": "2022-07-29T21:54:12+0000", - "dateFinished": "2022-07-29T21:54:12+0000", - "status": "FINISHED", - "$$hashKey": "object:41" - }, - { - "text": "%md\n# Using the Wikipedia model as an example\n\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:54:12+0000", - "progress": 0, - "config": { - "tableHide": false, - "editorSetting": { - "language": "md", - "editOnDblClick": false, - "completionKey": "TAB", - "completionSupport": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Using the Wikipedia model as an example

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_-1917632023", - "id": "20220729-215332_1279160828", - "dateCreated": "2021-02-17T07:36:05+0000", - "dateStarted": "2022-07-29T21:54:12+0000", - "dateFinished": "2022-07-29T21:54:12+0000", - "status": "FINISHED", - "$$hashKey": "object:42" - }, - { - "title": "Delete existing policies and create new policies for the Wiki Lexer", - "text": "%python\n\n# Should be executed in a separate session, otherwise it will not work\n# Specify settings for the Policy\ncur = cursor()\ncur.execute(\"BEGIN ctx_ddl.drop_policy('wiki_txtpol'); EXCEPTION WHEN OTHERS THEN NULL; END;\")\ncur.execute(\"BEGIN ctx_ddl.drop_preference( 'wiki_lexer'); EXCEPTION WHEN OTHERS THEN NULL; END;\")\ncur.execute(\"BEGIN ctx_ddl.create_preference('wiki_lexer', 'BASIC_LEXER'); END;\")\ncur.execute(\"BEGIN ctx_ddl.set_attribute('wiki_lexer', 'INDEX_STEMS', 'ENGLISH'); END;\")\ncur.execute(\"BEGIN ctx_ddl.create_policy(policy_name => 'wiki_txtpol', lexer => 'wiki_lexer'); END;\")\ncur.close()", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:54:12+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "editorHide": false, - "title": true, - "results": {}, - "enabled": false - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_-324344600", - "id": "20220729-215332_1017204134", - "dateCreated": "2021-02-18T02:03:31+0000", - "dateStarted": "2021-02-18T04:51:12+0000", - "dateFinished": "2021-02-18T04:51:13+0000", - "status": "FINISHED", - "$$hashKey": "object:43" - }, - { - "text": "%md \n\n### The pre-built Wikipedia model must be loaded to the Oracle Autonomous Database. It is a relatively large model object at 800 MB.\n#### Follow the setup in template notebook *OML Import ESA Wiki Model*\n\n#### Relevant Oracle blogs:\n1. New Wikipedia-Based Cognitive Model Available for Text Processing \n2. Text Analytics using a pre-built Wikipedia-based Topic Model \n3. Explicit Semantic Analysis (ESA) for Text Analytics \n\nWe will also need to create a model proxy object for the Wiki model into OML4R\n - Use the included function ore.createESA.wiki_model() to create our proxy object\n - This function retrieves information about the Wikipedia model and uses that information to create our ESA model using the ore.odmESA function\n\nWe need to create the proxy for the existing model into OML4Py\n - If the model is available on the same user, you can use the code:\n In Python: \"esa_wiki_mod = oml.esa(model_name = 'in-db wiki modelname') \"\n - If the model is available on a different schema, you need to:\n 1. Run as SYSDBA a \"grant execute on model to or public\" in sql; then\n 2. In Python \"esa_wiki_mod = oml.esa(model_name = 'in-db wiki modelname', model_owner = 'model owner schema name') \"", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:54:13+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

The pre-built Wikipedia model must be loaded to the Oracle Autonomous Database. It is a relatively large model object at 800 MB.

\n

Follow the setup in template notebook OML Import ESA Wiki Model

\n

Relevant Oracle blogs:

\n
    \n
  1. New Wikipedia-Based Cognitive Model Available for Text Processing
    2. \n
  2. Text Analytics using a pre-built Wikipedia-based Topic Model
    3. \n
  3. Explicit Semantic Analysis (ESA) for Text Analytics
    4. \n
\n

We will also need to create a model proxy object for the Wiki model into OML4R

\n\n

We need to create the proxy for the existing model into OML4Py

\n\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_-219897430", - "id": "20220729-215332_1509137468", - "dateCreated": "2021-02-17T20:50:44+0000", - "dateStarted": "2022-07-29T21:54:13+0000", - "dateFinished": "2022-07-29T21:54:13+0000", - "status": "FINISHED", - "$$hashKey": "object:44" - }, - { - "title": "Import libraries", - "text": "%python\n\nimport oml\nimport pandas as pd\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:54:13+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_1385856998", - "id": "20220729-215332_1270760679", - "dateCreated": "2021-07-15T22:16:39+0000", - "dateStarted": "2022-07-29T21:54:13+0000", - "dateFinished": "2022-07-29T21:54:23+0000", - "status": "FINISHED", - "$$hashKey": "object:45" - }, - { - "title": "Check to see if the pre-loaded model is available", - "text": "%sql\n\n-- We should expect one row with the model WIKI_MODEL\nselect MODEL_NAME, MINING_FUNCTION, ALGORITHM, ALGORITHM_TYPE, CREATION_DATE from USER_MINING_MODELS where MODEL_NAME='WIKI_MODEL'\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:54:23+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 104.667, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "MODEL_NAME": "string", - "MINING_FUNCTION": "string", - "ALGORITHM": "string", - "ALGORITHM_TYPE": "string", - "CREATION_DATE": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "MODEL_NAME\tMINING_FUNCTION\tALGORITHM\tALGORITHM_TYPE\tCREATION_DATE\nWIKI_MODEL\tFEATURE_EXTRACTION\tEXPLICIT_SEMANTIC_ANALYS\tNATIVE\t2021-02-18 02:13:11\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_764989475", - "id": "20220729-215332_1949330941", - "dateCreated": "2021-02-18T04:58:16+0000", - "dateStarted": "2022-07-29T21:54:23+0000", - "dateFinished": "2022-07-29T21:54:26+0000", - "status": "FINISHED", - "$$hashKey": "object:46" - }, - { - "title": "Create an OML4Py proxy ESA model object for the pre-loaded Wikipedia model ", - "text": "%python\n\nesa_wiki_mod = oml.esa(model_name = 'wiki_model')", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:54:26+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_530376984", - "id": "20220729-215332_1120588448", - "dateCreated": "2021-02-17T22:42:42+0000", - "dateStarted": "2022-07-29T21:54:26+0000", - "dateFinished": "2022-07-29T21:54:33+0000", - "status": "FINISHED", - "$$hashKey": "object:47" - }, - { - "title": "Check the first 1,000 rows of the 21.7 mi rows of features", - "text": "%python\n\nz.show(esa_wiki_mod.features.head(1000).round(4))", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:54:33+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "FEATURE_ID": "string", - "ATTRIBUTE_NAME": "string", - "ATTRIBUTE_VALUE": "string", - "COEFFICIENT": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "FEATURE_ID\tATTRIBUTE_NAME\tATTRIBUTE_VALUE\tCOEFFICIENT\n'Amr ibn al-'As\tTEXT.AAS\tNone\t0.0382\n'Amr ibn al-'As\tTEXT.ABD\tNone\t0.0558\n'Amr ibn al-'As\tTEXT.ABDULLAH\tNone\t0.0383\n'Amr ibn al-'As\tTEXT.ABJAR\tNone\t0.0523\n'Amr ibn al-'As\tTEXT.ABU\tNone\t0.1191\n'Amr ibn al-'As\tTEXT.ABYSSINIA\tNone\t0.0695\n'Amr ibn al-'As\tTEXT.AGREE\tNone\t0.0303\n'Amr ibn al-'As\tTEXT.AH\tNone\t0.0259\n'Amr ibn al-'As\tTEXT.AJNADAYN\tNone\t0.0517\n'Amr ibn al-'As\tTEXT.ALABAMA\tNone\t0.1369\n'Amr ibn al-'As\tTEXT.ALEXANDRIA\tNone\t0.0552\n'Amr ibn al-'As\tTEXT.ALI\tNone\t0.1337\n'Amr ibn al-'As\tTEXT.ALLAH\tNone\t0.0555\n'Amr ibn al-'As\tTEXT.AMR\tNone\t0.6049\n'Amr ibn al-'As\tTEXT.ANWAR\tNone\t0.0304\n'Amr ibn al-'As\tTEXT.ARAB\tNone\t0.0825\n'Amr ibn al-'As\tTEXT.ARBITER\tNone\t0.0985\n'Amr ibn al-'As\tTEXT.ARI\tNone\t0.0281\n'Amr ibn al-'As\tTEXT.ARMAH\tNone\t0.0463\n'Amr ibn al-'As\tTEXT.ASHTAR\tNone\t0.0469\n'Amr ibn al-'As\tTEXT.AWIYA\tNone\t0.0452\n'Amr ibn al-'As\tTEXT.AWIYAH\tNone\t0.3036\n'Amr ibn al-'As\tTEXT.BABYLON\tNone\t0.0516\n'Amr ibn al-'As\tTEXT.BAKR\tNone\t0.066\n'Amr ibn al-'As\tTEXT.BANU\tNone\t0.0331\n'Amr ibn al-'As\tTEXT.BEHOLD\tNone\t0.0302\n'Amr ibn al-'As\tTEXT.BILBEIS\tNone\t0.0499\n'Amr ibn al-'As\tTEXT.BINT\tNone\t0.0539\n'Amr ibn al-'As\tTEXT.BYZANTINE\tNone\t0.0714\n'Amr ibn al-'As\tTEXT.CAIRO\tNone\t0.0354\n'Amr ibn al-'As\tTEXT.CALIPH\tNone\t0.0558\n'Amr ibn al-'As\tTEXT.CALIPHATE\tNone\t0.0412\n'Amr ibn al-'As\tTEXT.CARAVAN\tNone\t0.0255\n'Amr ibn al-'As\tTEXT.CAREFUL\tNone\t0.0207\n'Amr ibn al-'As\tTEXT.CONQUEST\tNone\t0.0653\n'Amr ibn al-'As\tTEXT.CONTINGENT\tNone\t0.0218\n'Amr ibn al-'As\tTEXT.COPT\tNone\t0.0461\n'Amr ibn al-'As\tTEXT.COPTIC\tNone\t0.0296\n'Amr ibn al-'As\tTEXT.DAMASCUS\tNone\t0.0397\n'Amr ibn al-'As\tTEXT.DEALING\tNone\t0.026\n'Amr ibn al-'As\tTEXT.DELEGATION\tNone\t0.0201\n'Amr ibn al-'As\tTEXT.DEPOSE\tNone\t0.0214\n'Amr ibn al-'As\tTEXT.DESPICABLE\tNone\t0.0359\n'Amr ibn al-'As\tTEXT.DETERMINEDLY\tNone\t0.0424\n'Amr ibn al-'As\tTEXT.DHAT\tNone\t0.0523\n'Amr ibn al-'As\tTEXT.DHUL\tNone\t0.0444\n'Amr ibn al-'As\tTEXT.DISTRUST\tNone\t0.0254\n'Amr ibn al-'As\tTEXT.EGYPT\tNone\t0.1236\n'Amr ibn al-'As\tTEXT.EGYPTIAN\tNone\t0.0646\n'Amr ibn al-'As\tTEXT.EIGHTY\tNone\t0.0207\n'Amr ibn al-'As\tTEXT.ENVOY\tNone\t0.0236\n'Amr ibn al-'As\tTEXT.FIRMLY\tNone\t0.0213\n'Amr ibn al-'As\tTEXT.FITNA\tNone\t0.0418\n'Amr ibn al-'As\tTEXT.FORTIFY\tNone\t0.02\n'Amr ibn al-'As\tTEXT.FUSTAT\tNone\t0.0634\n'Amr ibn al-'As\tTEXT.GLUBB\tNone\t0.0465\n'Amr ibn al-'As\tTEXT.HADITH\tNone\t0.0319\n'Amr ibn al-'As\tTEXT.HAGAR\tNone\t0.037\n'Amr ibn al-'As\tTEXT.HAJJAJ\tNone\t0.0428\n'Amr ibn al-'As\tTEXT.HELIOPOLIS\tNone\t0.0782\n'Amr ibn al-'As\tTEXT.HIJ\tNone\t0.0499\n'Amr ibn al-'As\tTEXT.HILF\tNone\t0.0503\n'Amr ibn al-'As\tTEXT.HISHAM\tNone\t0.0367\n'Amr ibn al-'As\tTEXT.HOSTILE\tNone\t0.0184\n'Amr ibn al-'As\tTEXT.IBN\tNone\t0.2922\n'Amr ibn al-'As\tTEXT.INVADER\tNone\t0.0332\n'Amr ibn al-'As\tTEXT.INVOKE\tNone\t0.0217\n'Amr ibn al-'As\tTEXT.JARRAH\tNone\t0.0396\n'Amr ibn al-'As\tTEXT.KHALID\tNone\t0.0447\n'Amr ibn al-'As\tTEXT.KHATTAB\tNone\t0.0588\n'Amr ibn al-'As\tTEXT.KIN\tNone\t0.0269\n'Amr ibn al-'As\tTEXT.KITH\tNone\t0.0455\n'Amr ibn al-'As\tTEXT.KULTHUM\tNone\t0.0447\n'Amr ibn al-'As\tTEXT.LASTLY\tNone\t0.0265\n'Amr ibn al-'As\tTEXT.MALIK\tNone\t0.0264\n'Amr ibn al-'As\tTEXT.MECCA\tNone\t0.04\n'Amr ibn al-'As\tTEXT.MEDINA\tNone\t0.0532\n'Amr ibn al-'As\tTEXT.MERCY\tNone\t0.0214\n'Amr ibn al-'As\tTEXT.MESSENGER\tNone\t0.022\n'Amr ibn al-'As\tTEXT.MOSQUE\tNone\t0.0745\n'Amr ibn al-'As\tTEXT.MU\tNone\t0.1725\n'Amr ibn al-'As\tTEXT.MUHAMMAD\tNone\t0.1018\n'Amr ibn al-'As\tTEXT.MUNABBIH\tNone\t0.0492\n'Amr ibn al-'As\tTEXT.MUSA\tNone\t0.1041\n'Amr ibn al-'As\tTEXT.MUSLIM\tNone\t0.097\n'Amr ibn al-'As\tTEXT.NEGUS\tNone\t0.0417\n'Amr ibn al-'As\tTEXT.NEITHER\tNone\t0.0258\n'Amr ibn al-'As\tTEXT.NILE\tNone\t0.0374\n'Amr ibn al-'As\tTEXT.OBLIGE\tNone\t0.0208\n'Amr ibn al-'As\tTEXT.OMAN\tNone\t0.0277\n'Amr ibn al-'As\tTEXT.OSAMA\tNone\t0.031\n'Amr ibn al-'As\tTEXT.PATRIARCH\tNone\t0.0233\n'Amr ibn al-'As\tTEXT.PATRONAGE\tNone\t0.0215\n'Amr ibn al-'As\tTEXT.PELUSIUM\tNone\t0.0447\n'Amr ibn al-'As\tTEXT.PRAY\tNone\t0.0209\n'Amr ibn al-'As\tTEXT.PROPHET\tNone\t0.0318\n'Amr ibn al-'As\tTEXT.QAIS\tNone\t0.043\n'Amr ibn al-'As\tTEXT.QAYS\tNone\t0.0625\n'Amr ibn al-'As\tTEXT.QUR\tNone\t0.0434\n'Amr ibn al-'As\tTEXT.QURAISH\tNone\t0.0463\n'Amr ibn al-'As\tTEXT.QURAN\tNone\t0.0423\n'Amr ibn al-'As\tTEXT.QURAYSH\tNone\t0.1565\n'Amr ibn al-'As\tTEXT.REAPPOINT\tNone\t0.0314\n'Amr ibn al-'As\tTEXT.RETORT\tNone\t0.0302\n'Amr ibn al-'As\tTEXT.RIGHTEOUS\tNone\t0.0266\n'Amr ibn al-'As\tTEXT.RULER\tNone\t0.0385\n'Amr ibn al-'As\tTEXT.SAHABA\tNone\t0.0626\n'Amr ibn al-'As\tTEXT.SAHM\tNone\t0.044\n'Amr ibn al-'As\tTEXT.SHREWD\tNone\t0.0311\n'Amr ibn al-'As\tTEXT.SIFFIN\tNone\t0.1438\n'Amr ibn al-'As\tTEXT.SINAI\tNone\t0.0267\n'Amr ibn al-'As\tTEXT.SKIRMISH\tNone\t0.0234\n'Amr ibn al-'As\tTEXT.SPEAR\tNone\t0.0219\n'Amr ibn al-'As\tTEXT.STIR\tNone\t0.0227\n'Amr ibn al-'As\tTEXT.SUNNAH\tNone\t0.0365\n'Amr ibn al-'As\tTEXT.SUNNI\tNone\t0.0255\n'Amr ibn al-'As\tTEXT.SURELY\tNone\t0.0266\n'Amr ibn al-'As\tTEXT.SYRIA\tNone\t0.0305\n'Amr ibn al-'As\tTEXT.TENT\tNone\t0.0227\n'Amr ibn al-'As\tTEXT.THEODORUS\tNone\t0.0396\n'Amr ibn al-'As\tTEXT.TOWARDS\tNone\t0.0208\n'Amr ibn al-'As\tTEXT.UBAIDAH\tNone\t0.0469\n'Amr ibn al-'As\tTEXT.UHUD\tNone\t0.0457\n'Amr ibn al-'As\tTEXT.UMAR\tNone\t0.1218\n'Amr ibn al-'As\tTEXT.UMM\tNone\t0.0341\n'Amr ibn al-'As\tTEXT.UQBA\tNone\t0.0436\n'Amr ibn al-'As\tTEXT.UTHMAN\tNone\t0.0362\n'Amr ibn al-'As\tTEXT.VERDICT\tNone\t0.0355\n'Amr ibn al-'As\tTEXT.WALID\tNone\t0.0512\n'Amr ibn al-'As\tTEXT.WICKED\tNone\t0.025\n'Amr ibn al-'As\tTEXT.WITHSTAND\tNone\t0.0229\n'Amr ibn al-'As\tTEXT.YAMAN\tNone\t0.0416\n'Amr ibn al-'As\tTEXT.YARMOUK\tNone\t0.042\n'Ndrangheta\tTEXT.ACTIVITY\tNone\t0.0276\n'Ndrangheta\tTEXT.ADORATION\tNone\t0.011\n'Ndrangheta\tTEXT.ALESSANDRO\tNone\t0.0093\n'Ndrangheta\tTEXT.AMPLE\tNone\t0.009\n'Ndrangheta\tTEXT.ANARCHIC\tNone\t0.0126\n'Ndrangheta\tTEXT.ANTIMAFIA\tNone\t0.0433\n'Ndrangheta\tTEXT.APULIAN\tNone\t0.0151\n'Ndrangheta\tTEXT.ARGENTINIAN\tNone\t0.0105\n'Ndrangheta\tTEXT.ARREST\tNone\t0.0571\n'Ndrangheta\tTEXT.ASPROMONTE\tNone\t0.017\n'Ndrangheta\tTEXT.AUC\tNone\t0.0146\n'Ndrangheta\tTEXT.BAKERY\tNone\t0.0095\n'Ndrangheta\tTEXT.BANDEROLE\tNone\t0.0185\n'Ndrangheta\tTEXT.BANDITRY\tNone\t0.0134\n'Ndrangheta\tTEXT.BARBARO\tNone\t0.0431\n'Ndrangheta\tTEXT.BEHAN\tNone\t0.0136\n'Ndrangheta\tTEXT.BENVENUTO\tNone\t0.0141\n'Ndrangheta\tTEXT.BERNARDO\tNone\t0.0099\n'Ndrangheta\tTEXT.BKA\tNone\t0.025\n'Ndrangheta\tTEXT.BLACKMAIL\tNone\t0.0142\n'Ndrangheta\tTEXT.BND\tNone\t0.0159\n'Ndrangheta\tTEXT.BOCCIA\tNone\t0.017\n'Ndrangheta\tTEXT.BONANNO\tNone\t0.0211\n'Ndrangheta\tTEXT.BOSS\tNone\t0.0519\n'Ndrangheta\tTEXT.BROKERAGE\tNone\t0.0112\n'Ndrangheta\tTEXT.BUNDESKRIMINALAMT\tNone\t0.0185\n'Ndrangheta\tTEXT.BUNDESNACHRICHTENDIENST\tNone\t0.0173\n'Ndrangheta\tTEXT.CALABRIA\tNone\t0.2175\n'Ndrangheta\tTEXT.CALABRIAN\tNone\t0.0761\n'Ndrangheta\tTEXT.CAMORRA\tNone\t0.0455\n'Ndrangheta\tTEXT.CANNED\tNone\t0.0107\n'Ndrangheta\tTEXT.CANS\tNone\t0.0106\n'Ndrangheta\tTEXT.CANTO\tNone\t0.0106\n'Ndrangheta\tTEXT.CAPO\tNone\t0.0101\n'Ndrangheta\tTEXT.CARMINE\tNone\t0.011\n'Ndrangheta\tTEXT.CARTEL\tNone\t0.0155\n'Ndrangheta\tTEXT.CATANZARO\tNone\t0.0154\n'Ndrangheta\tTEXT.CENTRO\tNone\t0.0097\n'Ndrangheta\tTEXT.CISTERNA\tNone\t0.0161\n'Ndrangheta\tTEXT.CLAN\tNone\t0.1028\n'Ndrangheta\tTEXT.CLANDESTINE\tNone\t0.0095\n'Ndrangheta\tTEXT.COCAINE\tNone\t0.1202\n'Ndrangheta\tTEXT.COHESION\tNone\t0.01\n'Ndrangheta\tTEXT.COLLEGIAL\tNone\t0.0137\n'Ndrangheta\tTEXT.COLOMBIAN\tNone\t0.0095\n'Ndrangheta\tTEXT.COMMISSIONE\tNone\t0.0173\n'Ndrangheta\tTEXT.CONTRABAND\tNone\t0.0117\n'Ndrangheta\tTEXT.CORONA\tNone\t0.0102\n'Ndrangheta\tTEXT.CORRADO\tNone\t0.0127\n'Ndrangheta\tTEXT.CORRIERE\tNone\t0.0138\n'Ndrangheta\tTEXT.COSA\tNone\t0.0383\n'Ndrangheta\tTEXT.COSENZA\tNone\t0.0226\n'Ndrangheta\tTEXT.COSIMO\tNone\t0.0247\n'Ndrangheta\tTEXT.COSMIN\tNone\t0.0163\n'Ndrangheta\tTEXT.COUNCILORS\tNone\t0.0168\n'Ndrangheta\tTEXT.COURAGEOUS\tNone\t0.0099\n'Ndrangheta\tTEXT.CRIME\tNone\t0.0545\n'Ndrangheta\tTEXT.CRIMINAL\tNone\t0.0416\n'Ndrangheta\tTEXT.DEALERSHIP\tNone\t0.01\n'Ndrangheta\tTEXT.DEFIANT\tNone\t0.0108\n'Ndrangheta\tTEXT.DIA\tNone\t0.0114\n'Ndrangheta\tTEXT.DICKIE\tNone\t0.0115\n'Ndrangheta\tTEXT.DIENST\tNone\t0.0153\n'Ndrangheta\tTEXT.DIREZIONE\tNone\t0.0179\n'Ndrangheta\tTEXT.DISASSEMBLE\tNone\t0.0109\n'Ndrangheta\tTEXT.DNR\tNone\t0.0235\n'Ndrangheta\tTEXT.DOMENICO\tNone\t0.0153\n'Ndrangheta\tTEXT.DOSSIER\tNone\t0.0117\n'Ndrangheta\tTEXT.DOUGH\tNone\t0.0112\n'Ndrangheta\tTEXT.DRUG\tNone\t0.0586\n'Ndrangheta\tTEXT.ECSTASY\tNone\t0.0156\n'Ndrangheta\tTEXT.EDITORE\tNone\t0.0125\n'Ndrangheta\tTEXT.EMCDDA\tNone\t0.0187\n'Ndrangheta\tTEXT.ERNESTO\tNone\t0.0154\n'Ndrangheta\tTEXT.EUROPOL\tNone\t0.0234\n'Ndrangheta\tTEXT.EUROS\tNone\t0.0096\n'Ndrangheta\tTEXT.EXCOMMUNICATE\tNone\t0.0102\n'Ndrangheta\tTEXT.EXCOMMUNICATION\tNone\t0.0111\n'Ndrangheta\tTEXT.EXONERATE\tNone\t0.0104\n'Ndrangheta\tTEXT.EXPORTATION\tNone\t0.0129\n'Ndrangheta\tTEXT.EXTORT\tNone\t0.0112\n'Ndrangheta\tTEXT.EXTORTION\tNone\t0.0425\n'Ndrangheta\tTEXT.EXTRADITE\tNone\t0.0114\n'Ndrangheta\tTEXT.EXTRADITION\tNone\t0.0167\n'Ndrangheta\tTEXT.FABIO\tNone\t0.0106\n'Ndrangheta\tTEXT.FAMILIAL\tNone\t0.0101\n'Ndrangheta\tTEXT.FEDERICO\tNone\t0.0096\n'Ndrangheta\tTEXT.FINANZA\tNone\t0.0158\n'Ndrangheta\tTEXT.FOOTSTEP\tNone\t0.009\n'Ndrangheta\tTEXT.FORGIONE\tNone\t0.0172\n'Ndrangheta\tTEXT.FORMIGONI\tNone\t0.0187\n'Ndrangheta\tTEXT.FRANCESCO\tNone\t0.0205\n'Ndrangheta\tTEXT.FRAUDULENT\tNone\t0.0097\n'Ndrangheta\tTEXT.FRAUENFELD\tNone\t0.0247\n'Ndrangheta\tTEXT.FREEMASONRY\tNone\t0.0117\n'Ndrangheta\tTEXT.FUGITIVE\tNone\t0.0129\n'Ndrangheta\tTEXT.GAMBINO\tNone\t0.026\n'Ndrangheta\tTEXT.GANGLAND\tNone\t0.0141\n'Ndrangheta\tTEXT.GETTY\tNone\t0.0108\n'Ndrangheta\tTEXT.GIOIA\tNone\t0.0199\n'Ndrangheta\tTEXT.GIORGI\tNone\t0.0128\n'Ndrangheta\tTEXT.GIOVANI\tNone\t0.0151\n'Ndrangheta\tTEXT.GIUSEPPE\tNone\t0.0289\n'Ndrangheta\tTEXT.GODFATHER\tNone\t0.0091\n'Ndrangheta\tTEXT.GONZI\tNone\t0.0542\n'Ndrangheta\tTEXT.GRASSO\tNone\t0.0149\n'Ndrangheta\tTEXT.GUARDIA\tNone\t0.0115\n'Ndrangheta\tTEXT.GUIDO\tNone\t0.0147\n'Ndrangheta\tTEXT.HANDOVER\tNone\t0.0112\n'Ndrangheta\tTEXT.HELVETICA\tNone\t0.0145\n'Ndrangheta\tTEXT.HEROIN\tNone\t0.0141\n'Ndrangheta\tTEXT.HEROISM\tNone\t0.0104\n'Ndrangheta\tTEXT.HIERARCHICAL\tNone\t0.0092\n'Ndrangheta\tTEXT.HIERARCHICALLY\tNone\t0.0134\n'Ndrangheta\tTEXT.HODDER\tNone\t0.0112\n'Ndrangheta\tTEXT.HOMICIDE\tNone\t0.0092\n'Ndrangheta\tTEXT.IBERIAN\tNone\t0.0091\n'Ndrangheta\tTEXT.ILLICIT\tNone\t0.0144\n'Ndrangheta\tTEXT.ILVA\tNone\t0.0185\n'Ndrangheta\tTEXT.IMPORTATION\tNone\t0.01\n'Ndrangheta\tTEXT.IMPORTER\tNone\t0.0103\n'Ndrangheta\tTEXT.INCONSPICUOUS\tNone\t0.0129\n'Ndrangheta\tTEXT.INDICTABLE\tNone\t0.0289\n'Ndrangheta\tTEXT.INDICTMENT\tNone\t0.0094\n'Ndrangheta\tTEXT.INFILTRATE\tNone\t0.0212\n'Ndrangheta\tTEXT.INFILTRATION\tNone\t0.0299\n'Ndrangheta\tTEXT.INTIMIDATION\tNone\t0.0095\n'Ndrangheta\tTEXT.IONIAN\tNone\t0.011\n'Ndrangheta\tTEXT.IONIC\tNone\t0.0102\n'Ndrangheta\tTEXT.IRREGULARITY\tNone\t0.0094\n'Ndrangheta\tTEXT.ITALIAN\tNone\t0.0643\n'Ndrangheta\tTEXT.ITALIANO\tNone\t0.0181\n'Ndrangheta\tTEXT.ITALY\tNone\t0.0737\n'Ndrangheta\tTEXT.JOERG\tNone\t0.0171\n'Ndrangheta\tTEXT.KANTON\tNone\t0.0166\n'Ndrangheta\tTEXT.KIDNAPPING\tNone\t0.0121\n'Ndrangheta\tTEXT.KILOGRAM\tNone\t0.0099\n'Ndrangheta\tTEXT.KIN\tNone\t0.0095\n'Ndrangheta\tTEXT.KLAUS\tNone\t0.0091\n'Ndrangheta\tTEXT.LAMPE\tNone\t0.0143\n'Ndrangheta\tTEXT.LAUNDER\tNone\t0.0758\n'Ndrangheta\tTEXT.LEGITIMATIZE\tNone\t0.0094\n'Ndrangheta\tTEXT.LEGITIMATIZING\tNone\t0.0126\n'Ndrangheta\tTEXT.LEGITIMIZE\tNone\t0.0101\n'Ndrangheta\tTEXT.LETIZIA\tNone\t0.0149\n'Ndrangheta\tTEXT.LIBRI\tNone\t0.012\n'Ndrangheta\tTEXT.LINCHPIN\tNone\t0.014\n'Ndrangheta\tTEXT.LOCALE\tNone\t0.0233\n'Ndrangheta\tTEXT.LOCRI\tNone\t0.0245\n'Ndrangheta\tTEXT.LOMBARDY\tNone\t0.0216\n'Ndrangheta\tTEXT.LUCA\tNone\t0.0484\n'Ndrangheta\tTEXT.LUMIA\tNone\t0.0161\n'Ndrangheta\tTEXT.MAFIA\tNone\t0.1143\n'Ndrangheta\tTEXT.MAFIOSA\tNone\t0.0187\n'Ndrangheta\tTEXT.MAFIOSO\tNone\t0.02\n'Ndrangheta\tTEXT.MANCUSO\tNone\t0.0145\n'Ndrangheta\tTEXT.MANLY\tNone\t0.0106\n'Ndrangheta\tTEXT.MATERIALIZED\tNone\t0.0117\n'Ndrangheta\tTEXT.METICULOUSLY\tNone\t0.0112\n'Ndrangheta\tTEXT.NARCOTIC\tNone\t0.0097\n'Ndrangheta\tTEXT.NATIONALE\tNone\t0.0096\n'Ndrangheta\tTEXT.NDRANGHETA\tNone\t0.8657\n'Ndrangheta\tTEXT.NEAPOLITAN\tNone\t0.0166\n'Ndrangheta\tTEXT.NOSTRA\tNone\t0.0368\n'Ndrangheta\tTEXT.OBEDIENCE\tNone\t0.0094\n'Ndrangheta\tTEXT.ONORATA\tNone\t0.0185\n'Ndrangheta\tTEXT.ONORE\tNone\t0.0234\n'Ndrangheta\tTEXT.OPERAZIONE\tNone\t0.0175\n'Ndrangheta\tTEXT.ORDEAL\tNone\t0.0101\n'Ndrangheta\tTEXT.ORLOVA\tNone\t0.0166\n'Ndrangheta\tTEXT.OVERHEAR\tNone\t0.0098\n'Ndrangheta\tTEXT.PADRINO\tNone\t0.0179\n'Ndrangheta\tTEXT.PALMI\tNone\t0.017\n'Ndrangheta\tTEXT.PAOLI\tNone\t0.0132\n'Ndrangheta\tTEXT.PARLOR\tNone\t0.0097\n'Ndrangheta\tTEXT.PASQUALE\tNone\t0.0178\n'Ndrangheta\tTEXT.PASTRY\tNone\t0.0107\n'Ndrangheta\tTEXT.PDL\tNone\t0.014\n'Ndrangheta\tTEXT.PELLE\tNone\t0.0212\n'Ndrangheta\tTEXT.PELLEGRINI\tNone\t0.0135\n'Ndrangheta\tTEXT.PENTITO\tNone\t0.0168\n'Ndrangheta\tTEXT.PESCE\tNone\t0.0156\n'Ndrangheta\tTEXT.PIEDMONT\tNone\t0.0094\n'Ndrangheta\tTEXT.PIERO\tNone\t0.0107\n'Ndrangheta\tTEXT.PILL\tNone\t0.0135\n'Ndrangheta\tTEXT.PINO\tNone\t0.0117\n'Ndrangheta\tTEXT.PIZZERIA\tNone\t0.0131\n'Ndrangheta\tTEXT.POLLINO\tNone\t0.0185\n'Ndrangheta\tTEXT.PREEMINENCE\tNone\t0.0131\n'Ndrangheta\tTEXT.PREFECT\tNone\t0.0095\n'Ndrangheta\tTEXT.PRESTI\tNone\t0.0172\n'Ndrangheta\tTEXT.PRIMORDIAL\tNone\t0.0106\n'Ndrangheta\tTEXT.PRINCIPALE\tNone\t0.0169\n'Ndrangheta\tTEXT.PROSECUTOR\tNone\t0.0232\n'Ndrangheta\tTEXT.PROVINCIA\tNone\t0.0256\n'Ndrangheta\tTEXT.PYRAMIDAL\tNone\t0.0117\n'Ndrangheta\tTEXT.QUAIL\tNone\t0.0177\n'Ndrangheta\tTEXT.QUINTINO\tNone\t0.0166\n'Ndrangheta\tTEXT.RACKETEER\tNone\t0.0114\n'Ndrangheta\tTEXT.RAFFAELE\tNone\t0.0126\n'Ndrangheta\tTEXT.RCMP\tNone\t0.0127\n'Ndrangheta\tTEXT.RECHERCHE\tNone\t0.0125\n'Ndrangheta\tTEXT.REGGIO\tNone\t0.0652\n'Ndrangheta\tTEXT.RESULTANT\tNone\t0.0092\n'Ndrangheta\tTEXT.ROCCO\tNone\t0.0109\n'Ndrangheta\tTEXT.ROSMINI\tNone\t0.0176\n'Ndrangheta\tTEXT.ROTTERDAM\tNone\t0.0096\n'Ndrangheta\tTEXT.SACRA\tNone\t0.0124\n'Ndrangheta\tTEXT.SALVATORE\tNone\t0.0155\n'Ndrangheta\tTEXT.SANGU\tNone\t0.0266\n'Ndrangheta\tTEXT.SAW\tNone\t0.0108\n'Ndrangheta\tTEXT.SEAPORT\tNone\t0.0092\n'Ndrangheta\tTEXT.SECRECY\tNone\t0.0091\n'Ndrangheta\tTEXT.SEMINARA\tNone\t0.0185\n'Ndrangheta\tTEXT.SERGI\tNone\t0.015\n'Ndrangheta\tTEXT.SERUM\tNone\t0.0099\n'Ndrangheta\tTEXT.SHARKING\tNone\t0.0154\n'Ndrangheta\tTEXT.SHOTGUN\tNone\t0.0095\n'Ndrangheta\tTEXT.SICILIAN\tNone\t0.0575\n'Ndrangheta\tTEXT.SILENCER\tNone\t0.0136\n'Ndrangheta\tTEXT.SIMONETTA\tNone\t0.0157\n'Ndrangheta\tTEXT.SKIM\tNone\t0.024\n'Ndrangheta\tTEXT.SLAB\tNone\t0.0094\n'Ndrangheta\tTEXT.SLOVAK\tNone\t0.0144\n'Ndrangheta\tTEXT.SMUGGLE\tNone\t0.0321\n'Ndrangheta\tTEXT.SOTTO\tNone\t0.0135\n'Ndrangheta\tTEXT.SPARKASSE\tNone\t0.0167\n'Ndrangheta\tTEXT.STEFANO\tNone\t0.01\n'Ndrangheta\tTEXT.STIRLING\tNone\t0.0092\n'Ndrangheta\tTEXT.STOUGHTON\tNone\t0.0112\n'Ndrangheta\tTEXT.STRANGIO\tNone\t0.0374\n'Ndrangheta\tTEXT.SUBSTANTIATE\tNone\t0.0105\n'Ndrangheta\tTEXT.SUBUNIT\tNone\t0.0115\n'Ndrangheta\tTEXT.SUL\tNone\t0.0109\n'Ndrangheta\tTEXT.SUPERORDINATE\tNone\t0.0418\n'Ndrangheta\tTEXT.SUPERVISORY\tNone\t0.0102\n'Ndrangheta\tTEXT.SURACI\tNone\t0.0182\n'Ndrangheta\tTEXT.TARANTO\tNone\t0.0122\n'Ndrangheta\tTEXT.TAURO\tNone\t0.0245\n'Ndrangheta\tTEXT.THURINGIA\tNone\t0.0117\n'Ndrangheta\tTEXT.TRAFFIC\tNone\t0.045\n'Ndrangheta\tTEXT.TRANSATLANTIC\tNone\t0.0094\n'Ndrangheta\tTEXT.TRANSFERAL\tNone\t0.0165\n'Ndrangheta\tTEXT.TRANSNATIONAL\tNone\t0.0102\n'Ndrangheta\tTEXT.TUNA\tNone\t0.0107\n'Ndrangheta\tTEXT.TURIN\tNone\t0.0138\n'Ndrangheta\tTEXT.TYRRHENIAN\tNone\t0.0132\n'Ndrangheta\tTEXT.ULM\tNone\t0.012\n'Ndrangheta\tTEXT.UNDERCOVER\tNone\t0.0225\n'Ndrangheta\tTEXT.UNDERSCORE\tNone\t0.0101\n'Ndrangheta\tTEXT.UNEARTH\tNone\t0.0092\n'Ndrangheta\tTEXT.UNITA\tNone\t0.014\n'Ndrangheta\tTEXT.UNLICENSED\tNone\t0.0109\n'Ndrangheta\tTEXT.UNODC\tNone\t0.0151\n'Ndrangheta\tTEXT.UNPROFESSIONAL\tNone\t0.0127\n'Ndrangheta\tTEXT.UOMINI\tNone\t0.0157\n'Ndrangheta\tTEXT.URIBE\tNone\t0.0136\n'Ndrangheta\tTEXT.USURY\tNone\t0.0195\n'Ndrangheta\tTEXT.VALAIS\tNone\t0.0205\n'Ndrangheta\tTEXT.VALENTE\tNone\t0.0212\n'Ndrangheta\tTEXT.VALIANT\tNone\t0.0099\n'Ndrangheta\tTEXT.VARESE\tNone\t0.0133\n'Ndrangheta\tTEXT.WIKILEAKS\tNone\t0.0116\n'Ndrangheta\tTEXT.WIRETAP\tNone\t0.0116\n'Ndrangheta\tTEXT.WOODBRIDGE\tNone\t0.0165\n'Ndrangheta\tTEXT.ZETA\tNone\t0.0099\n'Pataphysics\tTEXT.ABERRATION\tNone\t0.0223\n'Pataphysics\tTEXT.ABSOLU\tNone\t0.0329\n'Pataphysics\tTEXT.ABSOLUTE\tNone\t0.0288\n'Pataphysics\tTEXT.ABSURDISM\tNone\t0.0315\n'Pataphysics\tTEXT.ACTUELLE\tNone\t0.032\n'Pataphysics\tTEXT.ADJECTIVE\tNone\t0.0165\n'Pataphysics\tTEXT.AGAMBEN\tNone\t0.0455\n'Pataphysics\tTEXT.ALFORTVILLE\tNone\t0.0347\n'Pataphysics\tTEXT.AMOK\tNone\t0.0258\n'Pataphysics\tTEXT.ANIMATRONIC\tNone\t0.0374\n'Pataphysics\tTEXT.ANOMALY\tNone\t0.0269\n'Pataphysics\tTEXT.ANTINOMY\tNone\t0.0493\n'Pataphysics\tTEXT.APOSTROPHE\tNone\t0.0463\n'Pataphysics\tTEXT.APPENDAGE\tNone\t0.0221\n'Pataphysics\tTEXT.ARBITRARY\tNone\t0.0151\n'Pataphysics\tTEXT.ARISTOTLE\tNone\t0.0168\n'Pataphysics\tTEXT.ARNAUD\tNone\t0.0222\n'Pataphysics\tTEXT.ARRABAL\tNone\t0.0315\n'Pataphysics\tTEXT.ARTICULATION\tNone\t0.019\n'Pataphysics\tTEXT.ASCENSION\tNone\t0.0164\n'Pataphysics\tTEXT.ASGER\tNone\t0.031\n'Pataphysics\tTEXT.AUTOLUX\tNone\t0.034\n'Pataphysics\tTEXT.AUTOMATON\tNone\t0.0244\n'Pataphysics\tTEXT.BAUDRILLARD\tNone\t0.0278\n'Pataphysics\tTEXT.BEAUMONT\tNone\t0.018\n'Pataphysics\tTEXT.BELLY\tNone\t0.0164\n'Pataphysics\tTEXT.BLANCHOT\tNone\t0.0633\n'Pataphysics\tTEXT.BLOOMSBURY\tNone\t0.019\n'Pataphysics\tTEXT.BOSSE\tNone\t0.0282\n'Pataphysics\tTEXT.BRASCHI\tNone\t0.0267\n'Pataphysics\tTEXT.BREWTON\tNone\t0.048\n'Pataphysics\tTEXT.BRYARS\tNone\t0.0452\n'Pataphysics\tTEXT.BUDAPEST\tNone\t0.0167\n'Pataphysics\tTEXT.BUENOS\tNone\t0.0162\n'Pataphysics\tTEXT.BUMBLE\tNone\t0.0215\n'Pataphysics\tTEXT.CAHIERS\tNone\t0.0236\n'Pataphysics\tTEXT.CAL\tNone\t0.0168\n'Pataphysics\tTEXT.CELESTIAL\tNone\t0.0169\n'Pataphysics\tTEXT.CHANDELIER\tNone\t0.0218\n'Pataphysics\tTEXT.CHESSBOARD\tNone\t0.0269\n'Pataphysics\tTEXT.CHICO\tNone\t0.0198\n'Pataphysics\tTEXT.CHIME\tNone\t0.0198\n'Pataphysics\tTEXT.CHIPMUNK\tNone\t0.0221\n'Pataphysics\tTEXT.CHRISTOPHE\tNone\t0.0302\n'Pataphysics\tTEXT.CLINAMEN\tNone\t0.0505\n'Pataphysics\tTEXT.CLOSET\tNone\t0.0181\n'Pataphysics\tTEXT.COLLEGIUM\tNone\t0.0232\n'Pataphysics\tTEXT.CONCEIT\tNone\t0.023\n'Pataphysics\tTEXT.CONCEPTUAL\tNone\t0.016\n'Pataphysics\tTEXT.CONSCIOUSLY\tNone\t0.0179\n'Pataphysics\tTEXT.CORBUSIER\tNone\t0.0238\n'Pataphysics\tTEXT.CROCODILE\tNone\t0.0182\n'Pataphysics\tTEXT.CURATED\tNone\t0.0188\n'Pataphysics\tTEXT.CURATOR\tNone\t0.0249\n'Pataphysics\tTEXT.CURIOSITY\tNone\t0.0169\n'Pataphysics\tTEXT.CZECHOSLOVAKIA\tNone\t0.0246\n'Pataphysics\tTEXT.DADA\tNone\t0.0208\n'Pataphysics\tTEXT.DIGEST\tNone\t0.0162\n'Pataphysics\tTEXT.DISAPPEARANCE\tNone\t0.0233\n'Pataphysics\tTEXT.DOGMA\tNone\t0.0189\n'Pataphysics\tTEXT.DOSSIER\tNone\t0.022\n'Pataphysics\tTEXT.DUALITY\tNone\t0.0206\n'Pataphysics\tTEXT.DUCHAMP\tNone\t0.0353\n'Pataphysics\tTEXT.EDISON\tNone\t0.0171\n'Pataphysics\tTEXT.ELEMENTARE\tNone\t0.034\n'Pataphysics\tTEXT.ENLARGER\tNone\t0.0317\n'Pataphysics\tTEXT.ESTEBAN\tNone\t0.0209\n'Pataphysics\tTEXT.EXHIBIT\tNone\t0.0277\n'Pataphysics\tTEXT.EXIST\tNone\t0.0204\n'Pataphysics\tTEXT.EXPRESSIONISM\tNone\t0.0217\n'Pataphysics\tTEXT.FAUST\tNone\t0.0196\n'Pataphysics\tTEXT.FERREIRA\tNone\t0.0219\n'Pataphysics\tTEXT.FIGURATIVE\tNone\t0.0294\n'Pataphysics\tTEXT.FIRESIGN\tNone\t0.0304\n'Pataphysics\tTEXT.FREAK\tNone\t0.0173\n'Pataphysics\tTEXT.GAVIN\tNone\t0.0246\n'Pataphysics\tTEXT.GENET\tNone\t0.025\n'Pataphysics\tTEXT.GESTATION\tNone\t0.0208\n'Pataphysics\tTEXT.GIANNINA\tNone\t0.0272\n'Pataphysics\tTEXT.GLIMPSE\tNone\t0.0172\n'Pataphysics\tTEXT.GRAFFITI\tNone\t0.0181\n'Pataphysics\tTEXT.GREGORIAN\tNone\t0.0373\n'Pataphysics\tTEXT.GROUCHO\tNone\t0.0237\n'Pataphysics\tTEXT.HA\tNone\t0.0227\n'Pataphysics\tTEXT.HAHA\tNone\t0.0297\n'Pataphysics\tTEXT.HARNESS\tNone\t0.0164\n'Pataphysics\tTEXT.HARPO\tNone\t0.026\n'Pataphysics\tTEXT.HEIGHTEN\tNone\t0.016\n'Pataphysics\tTEXT.HILLYER\tNone\t0.0431\n'Pataphysics\tTEXT.HIRSUTISM\tNone\t0.0331\n'Pataphysics\tTEXT.HOLOGRAPHIC\tNone\t0.0228\n'Pataphysics\tTEXT.HUGILL\tNone\t0.0779\n'Pataphysics\tTEXT.IMAGINARY\tNone\t0.091\n'Pataphysics\tTEXT.IMAGINATIVE\tNone\t0.0181\n'Pataphysics\tTEXT.INCOMPATIBLE\tNone\t0.0164\n'Pataphysics\tTEXT.INTERACTIVE\tNone\t0.0261\n'Pataphysics\tTEXT.INTERNATIONALIZATION\tNone\t0.0226\n'Pataphysics\tTEXT.IONESCO\tNone\t0.0398\n'Pataphysics\tTEXT.IST\tNone\t0.0206\n'Pataphysics\tTEXT.IUNIVERSE\tNone\t0.0267\n'Pataphysics\tTEXT.JARRY\tNone\t0.2995\n'Pataphysics\tTEXT.JEAN\tNone\t0.0344\n'Pataphysics\tTEXT.JORN\tNone\t0.0297\n'Pataphysics\tTEXT.JULIEN\tNone\t0.0187\n'Pataphysics\tTEXT.JUXTAPOSE\tNone\t0.0203\n'Pataphysics\tTEXT.KAFKA\tNone\t0.0223\n'Pataphysics\tTEXT.LENNON\tNone\t0.0171\n'Pataphysics\tTEXT.LESCURE\tNone\t0.0337\n'Pataphysics\tTEXT.LIL\tNone\t0.0182\n'Pataphysics\tTEXT.LINEAMENT\tNone\t0.0312\n'Pataphysics\tTEXT.LOPEZ\tNone\t0.0245\n'Pataphysics\tTEXT.LUC\tNone\t0.0179\n'Pataphysics\tTEXT.LUPTON\tNone\t0.0258\n'Pataphysics\tTEXT.MAGNIFICENCE\tNone\t0.0236\n'Pataphysics\tTEXT.MARCEL\tNone\t0.0239\n'Pataphysics\tTEXT.META\tNone\t0.0174\n'Pataphysics\tTEXT.METAFICTION\tNone\t0.0292\n'Pataphysics\tTEXT.METAPHOR\tNone\t0.101\n'Pataphysics\tTEXT.METAPHORICAL\tNone\t0.0417\n'Pataphysics\tTEXT.METAPHYSIC\tNone\t0.1053\n'Pataphysics\tTEXT.MINUS\tNone\t0.0163\n'Pataphysics\tTEXT.MIREILLE\tNone\t0.0257\n'Pataphysics\tTEXT.MOLLET\tNone\t0.0298\n'Pataphysics\tTEXT.MONTFORT\tNone\t0.0218\n'Pataphysics\tTEXT.MUSIQUE\tNone\t0.0208\n'Pataphysics\tTEXT.MUTUALLY\tNone\t0.0151\n'Pataphysics\tTEXT.MYRIAD\tNone\t0.0182\n'Pataphysics\tTEXT.NAGE\tNone\t0.0313\n'Pataphysics\tTEXT.NEOPHILOLOGUS\tNone\t0.0352\n'Pataphysics\tTEXT.NICKLE\tNone\t0.0288\n'Pataphysics\tTEXT.NIGHTINGALE\tNone\t0.0194\n'Pataphysics\tTEXT.NOTATION\tNone\t0.0166\n'Pataphysics\tTEXT.OCCULTATION\tNone\t0.0268\n'Pataphysics\tTEXT.OFFENBACH\tNone\t0.0233\n'Pataphysics\tTEXT.OFFSHOOT\tNone\t0.0171\n'Pataphysics\tTEXT.OLFACTORY\tNone\t0.0235\n'Pataphysics\tTEXT.ORACLE\tNone\t0.0172\n'Pataphysics\tTEXT.ORNAMENTATION\tNone\t0.02\n'Pataphysics\tTEXT.ORTHOGRAPHY\tNone\t0.0188\n'Pataphysics\tTEXT.OULIPO\tNone\t0.0337\n'Pataphysics\tTEXT.OUTLANDISH\tNone\t0.0218\n'Pataphysics\tTEXT.PA\tNone\t0.0183\n'Pataphysics\tTEXT.PABLO\tNone\t0.0229\n'Pataphysics\tTEXT.PARADOX\tNone\t0.0169\n'Pataphysics\tTEXT.PATAPHYSICS\tNone\t0.8162\n'Pataphysics\tTEXT.PATE\tNone\t0.0367\n'Pataphysics\tTEXT.PATTE\tNone\t0.032\n'Pataphysics\tTEXT.PEANUT\tNone\t0.0178\n'Pataphysics\tTEXT.PEIXOTO\tNone\t0.0305\n'Pataphysics\tTEXT.PERIPHERY\tNone\t0.0181\n'Pataphysics\tTEXT.PERRON\tNone\t0.0287\n'Pataphysics\tTEXT.PHYSIQUE\tNone\t0.0404\n'Pataphysics\tTEXT.PLASTICITY\tNone\t0.0233\n'Pataphysics\tTEXT.PRACTITIONER\tNone\t0.0211\n'Pataphysics\tTEXT.PRANK\tNone\t0.0188\n'Pataphysics\tTEXT.PREFERABLE\tNone\t0.019\n'Pataphysics\tTEXT.PROLEGOMENON\tNone\t0.0264\n'Pataphysics\tTEXT.PSEUDOSCIENCE\tNone\t0.0227\n'Pataphysics\tTEXT.PSYCHEDELIC\tNone\t0.0174\n'Pataphysics\tTEXT.PUN\tNone\t0.0479\n'Pataphysics\tTEXT.PURPORTEDLY\tNone\t0.018\n'Pataphysics\tTEXT.QUENEAU\tNone\t0.0449\n'Pataphysics\tTEXT.REALITY\tNone\t0.0356\n'Pataphysics\tTEXT.REALIZING\tNone\t0.0184\n'Pataphysics\tTEXT.RECONSTITUTE\tNone\t0.0177\n'Pataphysics\tTEXT.RECONSTRUCTIVE\tNone\t0.0238\n'Pataphysics\tTEXT.REITERATE\tNone\t0.0163\n'Pataphysics\tTEXT.RENE\tNone\t0.0194\n'Pataphysics\tTEXT.RENNES\tNone\t0.0231\n'Pataphysics\tTEXT.REPRESS\tNone\t0.0177\n'Pataphysics\tTEXT.REVUE\tNone\t0.0164\n'Pataphysics\tTEXT.RIDDLE\tNone\t0.0173\n'Pataphysics\tTEXT.RIGID\tNone\t0.0151\n'Pataphysics\tTEXT.ROI\tNone\t0.0195\n'Pataphysics\tTEXT.SABLE\tNone\t0.0199\n'Pataphysics\tTEXT.SAF\tNone\t0.0257\n'Pataphysics\tTEXT.SANDOMIR\tNone\t0.0337\n'Pataphysics\tTEXT.SEPARATION\tNone\t0.0287\n'Pataphysics\tTEXT.SERENDIPITY\tNone\t0.027\n'Pataphysics\tTEXT.SHATTUCK\tNone\t0.0403\n'Pataphysics\tTEXT.SIMILARITY\tNone\t0.0233\n'Pataphysics\tTEXT.SITUATIONIST\tNone\t0.027\n'Pataphysics\tTEXT.SLY\tNone\t0.0293\n'Pataphysics\tTEXT.SNORKEL\tNone\t0.0233\n'Pataphysics\tTEXT.SPECULATIVE\tNone\t0.017\n'Pataphysics\tTEXT.SPILLER\tNone\t0.027\n'Pataphysics\tTEXT.SPOOF\tNone\t0.0166\n'Pataphysics\tTEXT.STAROSTA\tNone\t0.0302\n'Pataphysics\tTEXT.STRIDE\tNone\t0.0176\n'Pataphysics\tTEXT.SUBCOMMITTEE\tNone\t0.0193\n'Pataphysics\tTEXT.SUBLIMINAL\tNone\t0.0247\n'Pataphysics\tTEXT.SUBTLE\tNone\t0.0146\n'Pataphysics\tTEXT.SUPPLEMENTARY\tNone\t0.0174\n'Pataphysics\tTEXT.SWERVE\tNone\t0.0346\n'Pataphysics\tTEXT.SYMBOLICALLY\tNone\t0.0186\n'Pataphysics\tTEXT.SYMMETRY\tNone\t0.0177\n'Pataphysics\tTEXT.SYNONYMOUS\tNone\t0.0153\n'Pataphysics\tTEXT.SYZYGY\tNone\t0.0615\n'Pataphysics\tTEXT.TA\tNone\t0.034\n'Pataphysics\tTEXT.TANYA\tNone\t0.0202\n'Pataphysics\tTEXT.TARA\tNone\t0.017\n'Pataphysics\tTEXT.TENUOUS\tNone\t0.0202\n'Pataphysics\tTEXT.TRANSCEND\tNone\t0.0176\n'Pataphysics\tTEXT.TRANSCENDENT\tNone\t0.0207\n'Pataphysics\tTEXT.TROLL\tNone\t0.0206\n'Pataphysics\tTEXT.TROPE\tNone\t0.0206\n'Pataphysics\tTEXT.TROUPE\tNone\t0.0247\n'Pataphysics\tTEXT.TUSCALOOSA\tNone\t0.023\n'Pataphysics\tTEXT.UBU\tNone\t0.0389\n'Pataphysics\tTEXT.UNDERTONE\tNone\t0.0218\n'Pataphysics\tTEXT.UNPREDICTABLE\tNone\t0.0173\n'Pataphysics\tTEXT.UNREALITY\tNone\t0.0271\n'Pataphysics\tTEXT.UNRELATED\tNone\t0.021\n'Pataphysics\tTEXT.UNSETTLE\tNone\t0.0186\n'Pataphysics\tTEXT.UNUSUALLY\tNone\t0.0208\n'Pataphysics\tTEXT.USELESS\tNone\t0.017\n'Pataphysics\tTEXT.VIAN\tNone\t0.0437\n'Pataphysics\tTEXT.VIGIL\tNone\t0.0199\n'Pataphysics\tTEXT.VILNIUS\tNone\t0.0315\n'Pataphysics\tTEXT.VIRTUALITY\tNone\t0.031\n'Pataphysics\tTEXT.VULGATE\tNone\t0.0222\n'Pataphysics\tTEXT.ZU\tNone\t0.0181\n'Til Death\tTEXT.AIRDATE\tNone\t0.0669\n'Til Death\tTEXT.AIRSTREAM\tNone\t0.1401\n'Til Death\tTEXT.ALISON\tNone\t0.0415\n'Til Death\tTEXT.ALLISON\tNone\t0.1654\n'Til Death\tTEXT.ALONGSIDE\tNone\t0.0347\n'Til Death\tTEXT.ATTRIBUTE\tNone\t0.0207\n'Til Death\tTEXT.BACKYARD\tNone\t0.0726\n'Til Death\tTEXT.BAKAY\tNone\t0.0846\n'Til Death\tTEXT.BARRY\tNone\t0.0411\n'Til Death\tTEXT.BATCH\tNone\t0.0821\n'Til Death\tTEXT.BETH\tNone\t0.0408\n'Til Death\tTEXT.BIODIESEL\tNone\t0.1215\n'Til Death\tTEXT.BOSTWICK\tNone\t0.0689\n'Til Death\tTEXT.BOYFRIEND\tNone\t0.0563\n'Til Death\tTEXT.BRAD\tNone\t0.0517\n'Til Death\tTEXT.BROAD\tNone\t0.0411\n'Til Death\tTEXT.CANCEL\tNone\t0.0451\n'Til Death\tTEXT.CANCELLED\tNone\t0.0678\n'Til Death\tTEXT.CATHY\tNone\t0.0472\n'Til Death\tTEXT.CHELTENHAM\tNone\t0.0498\n'Til Death\tTEXT.CHO\tNone\t0.0497\n'Til Death\tTEXT.CLERY\tNone\t0.1153\n'Til Death\tTEXT.COMPANION\tNone\t0.0274\n'Til Death\tTEXT.CONSIGN\tNone\t0.0562\n'Til Death\tTEXT.CONVINCE\tNone\t0.0221\n'Til Death\tTEXT.COPE\tNone\t0.0349\n'Til Death\tTEXT.COVET\tNone\t0.045\n'Til Death\tTEXT.DEATH\tNone\t0.0818\n'Til Death\tTEXT.DISCOUNT\tNone\t0.0375\n'Til Death\tTEXT.DISTURB\tNone\t0.0342\n'Til Death\tTEXT.DOESN\tNone\t0.0294\n'Til Death\tTEXT.DONNA\tNone\t0.0388\n'Til Death\tTEXT.DOUG\tNone\t0.1013\n'Til Death\tTEXT.DUFFY\tNone\t0.0454\n'Til Death\tTEXT.DVDS\tNone\t0.0633\n'Til Death\tTEXT.EDDIE\tNone\t0.236\n'Til Death\tTEXT.EPISODE\tNone\t0.2208\n'Til Death\tTEXT.EX\tNone\t0.0351\n'Til Death\tTEXT.EYE\tNone\t0.0274\n'Til Death\tTEXT.FINALE\tNone\t0.0329\n'Til Death\tTEXT.FISHER\tNone\t0.0498\n'Til Death\tTEXT.FOCUS\tNone\t0.0281\n'Til Death\tTEXT.FOSTER\tNone\t0.052\n'Til Death\tTEXT.FOUR\tNone\t0.022\n'Til Death\tTEXT.FOX\tNone\t0.0814\n'Til Death\tTEXT.FRESHMAN\tNone\t0.0351\n'Til Death\tTEXT.FRIDAYS\tNone\t0.0468\n'Til Death\tTEXT.FUN\tNone\t0.0296\n'Til Death\tTEXT.GARRETT\tNone\t0.0615\n'Til Death\tTEXT.GETTV\tNone\t0.0772\n'Til Death\tTEXT.GOLDSMITH\tNone\t0.0448\n'Til Death\tTEXT.HALT\tNone\t0.029\n'Til Death\tTEXT.HIATUS\tNone\t0.0354\n'Til Death\tTEXT.HIPPIE\tNone\t0.0473\n'Til Death\tTEXT.HUSBAND\tNone\t0.0362\n'Til Death\tTEXT.IDEALISTIC\tNone\t0.0508\n'Til Death\tTEXT.IDOL\tNone\t0.0337\n'Til Death\tTEXT.INITIALLY\tNone\t0.0263\n'Til Death\tTEXT.JEFF\tNone\t0.0662\n'Til Death\tTEXT.JOELY\tNone\t0.1094\n'Til Death\tTEXT.JOSH\tNone\t0.0339\n'Til Death\tTEXT.JOY\tNone\t0.1462\n'Til Death\tTEXT.KAT\tNone\t0.1018\n'Til Death\tTEXT.KATE\tNone\t0.0662\n'Til Death\tTEXT.KATHLEEN\tNone\t0.0397\n'Til Death\tTEXT.KAYE\tNone\t0.0949\n'Til Death\tTEXT.KAZAN\tNone\t0.05\n'Til Death\tTEXT.KENNY\tNone\t0.1045\n'Til Death\tTEXT.KRYSTEN\tNone\t0.1223\n'Til Death\tTEXT.KYM\tNone\t0.0633\n'Til Death\tTEXT.LAINIE\tNone\t0.0766\n'Til Death\tTEXT.LAMBERT\tNone\t0.0402\n'Til Death\tTEXT.LATE\tNone\t0.0079\n'Til Death\tTEXT.LAURA\tNone\t0.0502\n'Til Death\tTEXT.LINDSEY\tNone\t0.1167\n'Til Death\tTEXT.MAIN\tNone\t0.0334\n'Til Death\tTEXT.MANGANIELLO\tNone\t0.0789\n'Til Death\tTEXT.MAYWEATHER\tNone\t0.0676\n'Til Death\tTEXT.MICUCCI\tNone\t0.1631\n'Til Death\tTEXT.MULL\tNone\t0.056\n'Til Death\tTEXT.NEALON\tNone\t0.0744\n'Til Death\tTEXT.NEIGHBOR\tNone\t0.0278\n'Til Death\tTEXT.NEWLYWED\tNone\t0.084\n'Til Death\tTEXT.NICOLE\tNone\t0.0402\n'Til Death\tTEXT.OPTIMISTIC\tNone\t0.0433\n'Til Death\tTEXT.PAIR\tNone\t0.0304\n'Til Death\tTEXT.PERKIN\tNone\t0.0401\n'Til Death\tTEXT.PICK\tNone\t0.0295\n'Til Death\tTEXT.PLACA\tNone\t0.0879\n'Til Death\tTEXT.PREMISE\tNone\t0.0305\n'Til Death\tTEXT.PRINCIPAL\tNone\t0.0293\n'Til Death\tTEXT.PRODUCE\tNone\t0.0328\n'Til Death\tTEXT.PULL\tNone\t0.0223\n'Til Death\tTEXT.RATING\tNone\t0.1088\n'Til Death\tTEXT.RECUR\tNone\t0.1054\n'Til Death\tTEXT.RENEW\tNone\t0.0379\n'Til Death\tTEXT.RENEWAL\tNone\t0.0359\n'Til Death\tTEXT.RERUN\tNone\t0.0456\n'Til Death\tTEXT.RESPECTIVELY\tNone\t0.0264\n'Til Death\tTEXT.RITTER\tNone\t0.0722\n'Til Death\tTEXT.RUSS\tNone\t0.0439\n'Til Death\tTEXT.SARCASTIC\tNone\t0.051\n'Til Death\tTEXT.SASSO\tNone\t0.0665\n'Til Death\tTEXT.SCHEDULE\tNone\t0.027\n'Til Death\tTEXT.SEASON\tNone\t0.2898\n'Til Death\tTEXT.SEASONAL\tNone\t0.033\n'Til Death\tTEXT.SEPTEMBER\tNone\t0.0228\n'Til Death\tTEXT.SHARP\tNone\t0.0547\n'Til Death\tTEXT.SHOW\tNone\t0.0433\n'Til Death\tTEXT.SIMONA\tNone\t0.0632\n'Til Death\tTEXT.SIT-COM\tNone\t0.1009\n'Til Death\tTEXT.SLOT\tNone\t0.0336\n'Til Death\tTEXT.SMOOVE\tNone\t0.1946\n'Til Death\tTEXT.SONY\tNone\t0.0503\n'Til Death\tTEXT.SPIKE\tNone\t0.0355\n'Til Death\tTEXT.STAN\tNone\t0.0356\n'Til Death\tTEXT.STARK\tNone\t0.1713\n'Til Death\tTEXT.STARKS\tNone\t0.2351\n'Til Death\tTEXT.STEPH\tNone\t0.131\n'Til Death\tTEXT.STRAHAN\tNone\t0.0656\n'Til Death\tTEXT.STU\tNone\t0.0524\n'Til Death\tTEXT.SUBURBAN\tNone\t0.0307\n'Til Death\tTEXT.SURPRISE\tNone\t0.0224\n'Til Death\tTEXT.SYNDICATION\tNone\t0.0878\n'Til Death\tTEXT.THREE\tNone\t0.0119\n'Til Death\tTEXT.THURSDAYS\tNone\t0.0504\n'Til Death\tTEXT.TIL\tNone\t0.1235\n'Til Death\tTEXT.TIMM\tNone\t0.1246\n'Til Death\tTEXT.TINA\tNone\t0.0419\n'Til Death\tTEXT.TUCSON\tNone\t0.0467\n'Til Death\tTEXT.TYCOON\tNone\t0.0482\n'Til Death\tTEXT.UNAIRED\tNone\t0.0879\n'Til Death\tTEXT.UNEMPLOYED\tNone\t0.0404\n'Til Death\tTEXT.UPFRONT\tNone\t0.0582\n'Til Death\tTEXT.VIABLE\tNone\t0.0351\n'Til Death\tTEXT.VON\tNone\t0.0604\n'Til Death\tTEXT.WEDNESDAYS\tNone\t0.1024\n'Til Death\tTEXT.WESTCHESTER\tNone\t0.0743\n'Til Death\tTEXT.WGN\tNone\t0.0576\n'Til Death\tTEXT.WHITEY\tNone\t0.0573\n'Til Death\tTEXT.WHITLEY\tNone\t0.0543\n'Til Death\tTEXT.WIFE\tNone\t0.0328\n'Til Death\tTEXT.WOODCOCK\tNone\t0.1499\n'Til Death\tTEXT.XLIV\tNone\t0.0635\n'Til Death\tTEXT.YEAGLEY\tNone\t0.089\n'Tis Pity She's a Whore\tTEXT.ADAPTATION\tNone\t0.0428\n'Tis Pity She's a Whore\tTEXT.ADDIO\tNone\t0.0445\n'Tis Pity She's a Whore\tTEXT.ALAIN\tNone\t0.0258\n'Tis Pity She's a Whore\tTEXT.AMBIGUITY\tNone\t0.0257\n'Tis Pity She's a Whore\tTEXT.ANDERSSON\tNone\t0.0346\n'Tis Pity She's a Whore\tTEXT.ANGELIQUE\tNone\t0.0363\n'Tis Pity She's a Whore\tTEXT.ANNABELLA\tNone\t0.508\n'Tis Pity She's a Whore\tTEXT.APPRECIATION\tNone\t0.0215\n'Tis Pity She's a Whore\tTEXT.ARROGANT\tNone\t0.0272\n'Tis Pity She's a Whore\tTEXT.AVENGE\tNone\t0.0246\n'Tis Pity She's a Whore\tTEXT.BANDIT\tNone\t0.0381\n'Tis Pity She's a Whore\tTEXT.BANDITTI\tNone\t0.0492\n'Tis Pity She's a Whore\tTEXT.BANISH\tNone\t0.0252\n'Tis Pity She's a Whore\tTEXT.BARBICAN\tNone\t0.0492\n'Tis Pity She's a Whore\tTEXT.BEFRIEND\tNone\t0.0222\n'Tis Pity She's a Whore\tTEXT.BEG\tNone\t0.0222\n'Tis Pity She's a Whore\tTEXT.BETROTH\tNone\t0.0309\n'Tis Pity She's a Whore\tTEXT.BIBI\tNone\t0.0352\n'Tis Pity She's a Whore\tTEXT.BILLINGTON\tNone\t0.0362\n'Tis Pity She's a Whore\tTEXT.BLACKSTAR\tNone\t0.0466\n'Tis Pity She's a Whore\tTEXT.BOLOGNA\tNone\t0.026\n'Tis Pity She's a Whore\tTEXT.BONAVENTURA\tNone\t0.1035\n'Tis Pity She's a Whore\tTEXT.BOOKSELLER\tNone\t0.0303\n'Tis Pity She's a Whore\tTEXT.BOWIE\tNone\t0.0254\n'Tis Pity She's a Whore\tTEXT.BRT\tNone\t0.0354\n'Tis Pity She's a Whore\tTEXT.BUCKLEY\tNone\t0.0269\n'Tis Pity She's a Whore\tTEXT.CANDLELIGHT\tNone\t0.0345\n'Tis Pity She's a Whore\tTEXT.CARDINAL\tNone\t0.0531\n'Tis Pity She's a Whore\tTEXT.CHEAT\tNone\t0.0233\n'Tis Pity She's a Whore\tTEXT.CHEEK\tNone\t0.0248\n'Tis Pity She's a Whore\tTEXT.CHERIE\tNone\t0.0369\n'Tis Pity She's a Whore\tTEXT.COCKPIT\tNone\t0.0279\n'Tis Pity She's a Whore\tTEXT.CONDEMNATION\tNone\t0.0252\n'Tis Pity She's a Whore\tTEXT.CONFINE\tNone\t0.0184\n'Tis Pity She's a Whore\tTEXT.CONSUMMATE\tNone\t0.0294\n'Tis Pity She's a Whore\tTEXT.CONVENT\tNone\t0.0232\n'Tis Pity She's a Whore\tTEXT.CONVINCE\tNone\t0.0265\n'Tis Pity She's a Whore\tTEXT.CRANHAM\tNone\t0.0466\n'Tis Pity She's a Whore\tTEXT.CRUDELE\tNone\t0.0534\n'Tis Pity She's a Whore\tTEXT.DAMIEN\tNone\t0.0421\n'Tis Pity She's a Whore\tTEXT.DAMN\tNone\t0.0233\n'Tis Pity She's a Whore\tTEXT.DECLAN\tNone\t0.0506\n'Tis Pity She's a Whore\tTEXT.DELON\tNone\t0.0417\n'Tis Pity She's a Whore\tTEXT.DESPERATE\tNone\t0.0212\n'Tis Pity She's a Whore\tTEXT.DICE\tNone\t0.0298\n'Tis Pity She's a Whore\tTEXT.DISGUISE\tNone\t0.0203\n'Tis Pity She's a Whore\tTEXT.DISTRAUGHT\tNone\t0.0292\n'Tis Pity She's a Whore\tTEXT.DONNELLAN\tNone\t0.0882\n'Tis Pity She's a Whore\tTEXT.ESQUE\tNone\t0.0312\n'Tis Pity She's a Whore\tTEXT.EUPHEMISTIC\tNone\t0.0417\n'Tis Pity She's a Whore\tTEXT.FEAST\tNone\t0.0411\n'Tis Pity She's a Whore\tTEXT.FLORIO\tNone\t0.115\n'Tis Pity She's a Whore\tTEXT.FORD\tNone\t0.0538\n'Tis Pity She's a Whore\tTEXT.FRATELLO\tNone\t0.0442\n'Tis Pity She's a Whore\tTEXT.FRIAR\tNone\t0.0912\n'Tis Pity She's a Whore\tTEXT.FURIOUS\tNone\t0.0233\n'Tis Pity She's a Whore\tTEXT.GINA\tNone\t0.0288\n'Tis Pity She's a Whore\tTEXT.GIOVANNI\tNone\t0.2138\n'Tis Pity She's a Whore\tTEXT.GIUSEPPE\tNone\t0.0354\n'Tis Pity She's a Whore\tTEXT.GREENAWAY\tNone\t0.0381\n'Tis Pity She's a Whore\tTEXT.GRIFFI\tNone\t0.0782\n'Tis Pity She's a Whore\tTEXT.GRIMALDI\tNone\t0.129\n'Tis Pity She's a Whore\tTEXT.GUILT\tNone\t0.0237\n'Tis Pity She's a Whore\tTEXT.HATHITRUST\tNone\t0.0441\n'Tis Pity She's a Whore\tTEXT.HENRIETTA\tNone\t0.029\n'Tis Pity She's a Whore\tTEXT.HERSELF\tNone\t0.0309\n'Tis Pity She's a Whore\tTEXT.INCEST\tNone\t0.0477\n'Tis Pity She's a Whore\tTEXT.INCESTUOUS\tNone\t0.0532\n'Tis Pity She's a Whore\tTEXT.INCOMPLETE\tNone\t0.0212\n'Tis Pity She's a Whore\tTEXT.INSULT\tNone\t0.0207\n'Tis Pity She's a Whore\tTEXT.INTERVENE\tNone\t0.0189\n'Tis Pity She's a Whore\tTEXT.JACOBIAN\tNone\t0.0339\n'Tis Pity She's a Whore\tTEXT.JESSIE\tNone\t0.0272\n'Tis Pity She's a Whore\tTEXT.JOWL\tNone\t0.0442\n'Tis Pity She's a Whore\tTEXT.LONGHURST\tNone\t0.0424\n'Tis Pity She's a Whore\tTEXT.LUCHINO\tNone\t0.0398\n'Tis Pity She's a Whore\tTEXT.LUNGHI\tNone\t0.0499\n'Tis Pity She's a Whore\tTEXT.LYDIA\tNone\t0.0276\n'Tis Pity She's a Whore\tTEXT.MAETERLINCK\tNone\t0.0422\n'Tis Pity She's a Whore\tTEXT.MASQUE\tNone\t0.0331\n'Tis Pity She's a Whore\tTEXT.MEANWHILE\tNone\t0.0221\n'Tis Pity She's a Whore\tTEXT.MISTAKENLY\tNone\t0.0239\n'Tis Pity She's a Whore\tTEXT.MOB\tNone\t0.0214\n'Tis Pity She's a Whore\tTEXT.MOLONY\tNone\t0.0688\n'Tis Pity She's a Whore\tTEXT.MORDAUNT\tNone\t0.0414\n'Tis Pity She's a Whore\tTEXT.MUNBY\tNone\t0.0486\n'Tis Pity She's a Whore\tTEXT.NEWLYWED\tNone\t0.0336\n'Tis Pity She's a Whore\tTEXT.NIECE\tNone\t0.0342\n'Tis Pity She's a Whore\tTEXT.NOBLEMAN\tNone\t0.0269\n'Tis Pity She's a Whore\tTEXT.NUNCIO\tNone\t0.0353\n'Tis Pity She's a Whore\tTEXT.OBVIOUSLY\tNone\t0.0225\n'Tis Pity She's a Whore\tTEXT.OFFEND\tNone\t0.0226\n'Tis Pity She's a Whore\tTEXT.OKE\tNone\t0.0416\n'Tis Pity She's a Whore\tTEXT.OMIT\tNone\t0.0203\n'Tis Pity She's a Whore\tTEXT.ORMEROD\tNone\t0.0425\n'Tis Pity She's a Whore\tTEXT.PARAMOUR\tNone\t0.0399\n'Tis Pity She's a Whore\tTEXT.PARMA\tNone\t0.0875\n'Tis Pity She's a Whore\tTEXT.PASSIONATE\tNone\t0.023\n'Tis Pity She's a Whore\tTEXT.PATRONI\tNone\t0.076\n'Tis Pity She's a Whore\tTEXT.PAULINE\tNone\t0.0251\n'Tis Pity She's a Whore\tTEXT.PEPYS\tNone\t0.0346\n'Tis Pity She's a Whore\tTEXT.PETERBOROUGH\tNone\t0.0284\n'Tis Pity She's a Whore\tTEXT.PITTY\tNone\t0.0492\n'Tis Pity She's a Whore\tTEXT.PITY\tNone\t0.1433\n'Tis Pity She's a Whore\tTEXT.PLAYHOUSE\tNone\t0.0243\n'Tis Pity She's a Whore\tTEXT.POGGIO\tNone\t0.0593\n'Tis Pity She's a Whore\tTEXT.POISON\tNone\t0.0285\n'Tis Pity She's a Whore\tTEXT.PREGNANCY\tNone\t0.0336\n'Tis Pity She's a Whore\tTEXT.PRETEND\tNone\t0.0222\n'Tis Pity She's a Whore\tTEXT.PROPHECY\tNone\t0.0249\n'Tis Pity She's a Whore\tTEXT.QUARTO\tNone\t0.0362\n'Tis Pity She's a Whore\tTEXT.RAMPLING\tNone\t0.0412\n'Tis Pity She's a Whore\tTEXT.REPENT\tNone\t0.0315\n'Tis Pity She's a Whore\tTEXT.REPENTANCE\tNone\t0.0319\n'Tis Pity She's a Whore\tTEXT.REVEAL\tNone\t0.0281\n'Tis Pity She's a Whore\tTEXT.REVENGE\tNone\t0.0378\n'Tis Pity She's a Whore\tTEXT.REVIVE\tNone\t0.0227\n'Tis Pity She's a Whore\tTEXT.RID\tNone\t0.0234\n'Tis Pity She's a Whore\tTEXT.ROLAND\tNone\t0.0224\n'Tis Pity She's a Whore\tTEXT.ROMY\tNone\t0.0388\n'Tis Pity She's a Whore\tTEXT.SALISBURY\tNone\t0.0254\n'Tis Pity She's a Whore\tTEXT.SCEAUX\tNone\t0.0469\n'Tis Pity She's a Whore\tTEXT.SCHNEIDER\tNone\t0.0259\n'Tis Pity She's a Whore\tTEXT.SERVANT\tNone\t0.0342\n'Tis Pity She's a Whore\tTEXT.SHAFTESBURY\tNone\t0.0333\n'Tis Pity She's a Whore\tTEXT.SHEE\tNone\t0.0448\n'Tis Pity She's a Whore\tTEXT.SKEWER\tNone\t0.037\n'Tis Pity She's a Whore\tTEXT.SORANZO\tNone\t0.5007\n'Tis Pity She's a Whore\tTEXT.SPOUT\tNone\t0.0344\n'Tis Pity She's a Whore\tTEXT.STAB\tNone\t0.0587\n'Tis Pity She's a Whore\tTEXT.SUITOR\tNone\t0.0768\n'Tis Pity She's a Whore\tTEXT.SYLLABLE\tNone\t0.0254\n'Tis Pity She's a Whore\tTEXT.SYNOPSIS\tNone\t0.0264\n'Tis Pity She's a Whore\tTEXT.TALENTED\tNone\t0.0204\n'Tis Pity She's a Whore\tTEXT.TARANTINO\tNone\t0.0327\n'Tis Pity She's a Whore\tTEXT.TERRIBLE\tNone\t0.0209\n'Tis Pity She's a Whore\tTEXT.TI\tNone\t0.1584\n'Tis Pity She's a Whore\tTEXT.TOAST\tNone\t0.0279\n'Tis Pity She's a Whore\tTEXT.TOBIAS\tNone\t0.0288\n'Tis Pity She's a Whore\tTEXT.TUMULTUOUS\tNone\t0.0284\n'Tis Pity She's a Whore\tTEXT.TURVEY\tNone\t0.0441\n'Tis Pity She's a Whore\tTEXT.UNEDITED\tNone\t0.0347\n'Tis Pity She's a Whore\tTEXT.UNFORTUNATELY\tNone\t0.0191\n'Tis Pity She's a Whore\tTEXT.UNSETTLE\tNone\t0.0283\n'Tis Pity She's a Whore\tTEXT.UNSTOPPABLE\tNone\t0.0333\n'Tis Pity She's a Whore\tTEXT.VASQUES\tNone\t0.2401\n'Tis Pity She's a Whore\tTEXT.VERBALLY\tNone\t0.0421\n'Tis Pity She's a Whore\tTEXT.VICKERS\tNone\t0.0271\n'Tis Pity She's a Whore\tTEXT.VILLAINY\tNone\t0.0392\n'Tis Pity She's a Whore\tTEXT.VIRTUOUS\tNone\t0.0292\n'Tis Pity She's a Whore\tTEXT.VISCONTI\tNone\t0.0328\n'Tis Pity She's a Whore\tTEXT.VISUALLY\tNone\t0.0242\n'Tis Pity She's a Whore\tTEXT.WANAMAKER\tNone\t0.0368\n'Tis Pity She's a Whore\tTEXT.WHORE\tNone\t0.1592\n'Tis Pity She's a Whore\tTEXT.WIELD\tNone\t0.0238\n'Tis Pity She's a Whore\tTEXT.WILLINGLY\tNone\t0.0286\n's-Hertogenbosch\tTEXT.AA\tNone\t0.0357\n's-Hertogenbosch\tTEXT.ADEQUATE\tNone\t0.0193\n's-Hertogenbosch\tTEXT.ARCHERY\tNone\t0.0288\n's-Hertogenbosch\tTEXT.ARIE\tNone\t0.0302\n's-Hertogenbosch\tTEXT.ARRIVA\tNone\t0.0311\n's-Hertogenbosch\tTEXT.ATP\tNone\t0.0285\n's-Hertogenbosch\tTEXT.ATTRACTIVE\tNone\t0.019\n's-Hertogenbosch\tTEXT.BANDANA\tNone\t0.0409\n's-Hertogenbosch\tTEXT.BATAVIAN\tNone\t0.0367\n's-Hertogenbosch\tTEXT.BERLAYMONT\tNone\t0.049\n's-Hertogenbosch\tTEXT.BESIEGE\tNone\t0.0212\n's-Hertogenbosch\tTEXT.BIKE\tNone\t0.0409\n's-Hertogenbosch\tTEXT.BISHOPRIC\tNone\t0.0257\n's-Hertogenbosch\tTEXT.BOIS\tNone\t0.028\n's-Hertogenbosch\tTEXT.BONAPARTE\tNone\t0.027\n's-Hertogenbosch\tTEXT.BOSCH\tNone\t0.1779\n's-Hertogenbosch\tTEXT.BOSSCHE\tNone\t0.0477\n's-Hertogenbosch\tTEXT.BOZE\tNone\t0.049\n's-Hertogenbosch\tTEXT.BRABANT\tNone\t0.0781\n's-Hertogenbosch\tTEXT.BRABANTIAN\tNone\t0.0681\n's-Hertogenbosch\tTEXT.BRABANTINE\tNone\t0.0498\n's-Hertogenbosch\tTEXT.BREMNER\tNone\t0.038\n's-Hertogenbosch\tTEXT.BUSLINES\tNone\t0.0442\n's-Hertogenbosch\tTEXT.CALVINIST\tNone\t0.0286\n's-Hertogenbosch\tTEXT.CARNAVAL\tNone\t0.0368\n's-Hertogenbosch\tTEXT.CARNIVAL\tNone\t0.0544\n's-Hertogenbosch\tTEXT.CARTOGRAPHER\tNone\t0.031\n's-Hertogenbosch\tTEXT.CATASTROPHIC\tNone\t0.0247\n's-Hertogenbosch\tTEXT.CERAMIC\tNone\t0.0441\n's-Hertogenbosch\tTEXT.CFB\tNone\t0.0298\n's-Hertogenbosch\tTEXT.CHOCOLATE\tNone\t0.0233\n's-Hertogenbosch\tTEXT.CHRONICLER\tNone\t0.0257\n's-Hertogenbosch\tTEXT.CITY\tNone\t0.0803\n's-Hertogenbosch\tTEXT.CLASSICALISM\tNone\t0.0313\n's-Hertogenbosch\tTEXT.COLLOQUIAL\tNone\t0.0267\n's-Hertogenbosch\tTEXT.COLLOQUIALLY\tNone\t0.0226\n's-Hertogenbosch\tTEXT.CONFRATERNITY\tNone\t0.0373\n's-Hertogenbosch\tTEXT.CONTEMPORANEOUS\tNone\t0.0276\n's-Hertogenbosch\tTEXT.CONTRACTION\tNone\t0.0256\n's-Hertogenbosch\tTEXT.CONVENIENT\tNone\t0.0217\n's-Hertogenbosch\tTEXT.COPYIST\tNone\t0.0355\n's-Hertogenbosch\tTEXT.CRAFTSMAN\tNone\t0.0233\n's-Hertogenbosch\tTEXT.CREVECOEUR\tNone\t0.0494\n's-Hertogenbosch\tTEXT.CYCLIST\tNone\t0.0369\n's-Hertogenbosch\tTEXT.DEFENCE\tNone\t0.0235\n's-Hertogenbosch\tTEXT.DEN\tNone\t0.1135\n's-Hertogenbosch\tTEXT.DIMINISH\tNone\t0.0183\n's-Hertogenbosch\tTEXT.DISORDERLY\tNone\t0.0308\n's-Hertogenbosch\tTEXT.DIVERT\tNone\t0.0301\n's-Hertogenbosch\tTEXT.DONK\tNone\t0.0486\n's-Hertogenbosch\tTEXT.DONNER\tNone\t0.0333\n's-Hertogenbosch\tTEXT.DUC\tNone\t0.0307\n's-Hertogenbosch\tTEXT.DUNE\tNone\t0.0249\n's-Hertogenbosch\tTEXT.DUTCH\tNone\t0.0826\n's-Hertogenbosch\tTEXT.DYKE\tNone\t0.0262\n's-Hertogenbosch\tTEXT.EIGHTY\tNone\t0.0308\n's-Hertogenbosch\tTEXT.ENCROACHMENT\tNone\t0.0286\n's-Hertogenbosch\tTEXT.ENGELEN\tNone\t0.0524\n's-Hertogenbosch\tTEXT.ETHOLOGIST\tNone\t0.0415\n's-Hertogenbosch\tTEXT.FABRIC\tNone\t0.0217\n's-Hertogenbosch\tTEXT.FEMININ\tNone\t0.0524\n's-Hertogenbosch\tTEXT.FIERY\tNone\t0.0267\n's-Hertogenbosch\tTEXT.FOOTBALLER\tNone\t0.049\n's-Hertogenbosch\tTEXT.FORTIFICATION\tNone\t0.0413\n's-Hertogenbosch\tTEXT.FORTIFY\tNone\t0.0198\n's-Hertogenbosch\tTEXT.FORTRESS\tNone\t0.0554\n's-Hertogenbosch\tTEXT.FRAN\tNone\t0.0269\n's-Hertogenbosch\tTEXT.FREDERIK\tNone\t0.0306\n's-Hertogenbosch\tTEXT.FROG\tNone\t0.0233\n's-Hertogenbosch\tTEXT.GELRE\tNone\t0.0729\n's-Hertogenbosch\tTEXT.GENERALITY\tNone\t0.0339\n's-Hertogenbosch\tTEXT.GEO\tNone\t0.0274\n's-Hertogenbosch\tTEXT.GERARDUS\tNone\t0.0403\n's-Hertogenbosch\tTEXT.GERHARD\tNone\t0.026\n's-Hertogenbosch\tTEXT.GRASS\tNone\t0.0355\n's-Hertogenbosch\tTEXT.GREATLY\tNone\t0.0194\n's-Hertogenbosch\tTEXT.GRIET\tNone\t0.0517\n's-Hertogenbosch\tTEXT.HABSBURG\tNone\t0.049\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_-174474973", - "id": "20220729-215332_127775929", - "dateCreated": "2021-02-18T05:03:57+0000", - "dateStarted": "2022-07-29T21:54:33+0000", - "dateFinished": "2022-07-29T21:54:59+0000", - "status": "FINISHED", - "$$hashKey": "object:48" - }, - { - "title": "Basic settings of the ESA Wiki model and the 21.7 mi rows of features", - "text": "%python\n\nesa_wiki_mod.set_params", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:54:59+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "editorHide": false, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 364.667, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "FEATURE_ID": "string", - "ATTRIBUTE_NAME": "string", - "ATTRIBUTE_VALUE": "string", - "COEFFICIENT": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TEXT", - "data": "\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_539977268", - "id": "20220729-215332_1052594641", - "dateCreated": "2021-02-18T05:12:02+0000", - "dateStarted": "2022-07-29T21:54:59+0000", - "dateFinished": "2022-07-29T21:57:04+0000", - "status": "FINISHED", - "$$hashKey": "object:49" - }, - { - "text": "%md \n# Examples using the Wiki ESA model\n---", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:57:04+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Examples using the Wiki ESA model

\n
\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_-504309098", - "id": "20220729-215332_1226153086", - "dateCreated": "2021-02-18T05:22:27+0000", - "dateStarted": "2022-07-29T21:57:04+0000", - "dateFinished": "2022-07-29T21:57:04+0000", - "status": "FINISHED", - "$$hashKey": "object:50" - }, - { - "title": "Basic example of ESA features for the word 'Bank' using the Wikipedia model", - "text": "%python\n\ntemp_pd = oml.push(pd.DataFrame({'TEXT':['Bank']}))\nz.show(esa_wiki_mod.transform(temp_pd))\n\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:57:17+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "editorHide": false, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "FEATURE_ID": "string", - "VALUE": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - }, - "1": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "FEATURE_ID": "string", - "VALUE": "number" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TEXT", - "data": "UserWarning:Result is not pivoted because the feature number is larger than the pivot limit 100\n" - }, - { - "type": "TABLE", - "data": "FEATURE_ID\tVALUE\nBanking in Australia\t0.1315659582812627\nBank\t0.12849754351686726\nBank of America\t0.12473066375959004\nCentral bank\t0.1197576026968893\nBankBoston\t0.11536394616391579\nStandard Bank\t0.11380302918449736\nCommonwealth Bank\t0.10959263625942921\nBank of England\t0.1088084369470836\nBank run\t0.1065147243112437\nNational Provincial Bank\t0.10517066260609576\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_2095544009", - "id": "20220729-215332_1566447662", - "dateCreated": "2021-02-18T05:35:05+0000", - "dateStarted": "2022-07-29T21:57:04+0000", - "dateFinished": "2022-07-29T21:57:06+0000", - "status": "FINISHED", - "$$hashKey": "object:51" - }, - { - "title": "ESA Features for the words 'NFL games' using the Wikipedia model", - "text": "%python\n\ntemp_pd = oml.push(pd.DataFrame({'TEXT':['NFL Games']}))\nz.show(esa_wiki_mod.transform(temp_pd))\n\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:57:06+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "editorHide": false, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "FEATURE_ID": "string", - "VALUE": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "FEATURE_ID\tVALUE\nNFL Network\t0.14891764714401004\nNFL Films\t0.1353721055548557\nThe NFL Today\t0.12779327803336324\nNational Football League\t0.11940747887741375\nNFL Sunday Ticket\t0.117067625291956\nInside the NFL\t0.11163307758151528\nNFL International Series\t0.10738976731178129\nProfessional American football championship games\t0.10543738677657868\nNFL Europe\t0.09899840441087654\nNational Football League Draft\t0.09593817068270678\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_255734815", - "id": "20220729-215332_931944256", - "dateCreated": "2021-02-18T05:37:39+0000", - "dateStarted": "2022-07-29T21:57:06+0000", - "dateFinished": "2022-07-29T21:57:07+0000", - "status": "FINISHED", - "$$hashKey": "object:52" - }, - { - "title": "ESA Features for a text about Astronomy using the Wikipedia model", - "text": "%python\n\ntemp_pd = oml.push(pd.DataFrame({'TEXT':['A group of European-led astronomers has made a photograph of what appears to be a planet orbiting another star. If so, it would be the first confirmed picture of a world beyond our solar system.']}))\nz.show(esa_wiki_mod.transform(temp_pd))\n\n\n\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:57:07+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "editorHide": false, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "FEATURE_ID": "string", - "VALUE": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "FEATURE_ID\tVALUE\nFritz Haber\t0.1949371547650959\nSolar System\t0.175206654266355\nPlanetary system\t0.1749551660056489\nPlanet\t0.16589336764578985\nFormation and evolution of the Solar System\t0.1541314779936064\nSolar analog\t0.15350282500018386\nPlanets in science fiction\t0.13236270987318005\nPlanetary habitability\t0.1283266050843719\nExoplanet\t0.12227780960435798\nFirst Solar\t0.1190838726969703\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_2097390745", - "id": "20220729-215332_1676389305", - "dateCreated": "2021-02-18T05:31:47+0000", - "dateStarted": "2022-07-29T21:57:08+0000", - "dateFinished": "2022-07-29T21:57:09+0000", - "status": "FINISHED", - "$$hashKey": "object:53" - }, - { - "title": "ESA Features for a text about diet and health using the Wikipedia model", - "text": "%python\n\ntemp_pd = oml.push(pd.DataFrame({'TEXT':['Nearly 70 percent of Americans say they are careful about what they eat, and even more say diet is essential to good health, according to a new nationwide health poll in which obesity ranked second among the biggest health concerns.']}))\nz.show(esa_wiki_mod.transform(temp_pd))\n\n\n\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:57:09+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "editorHide": false, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - 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Yes, I''m inclined to agree, especially with regards to the historical relationship between stock prices and bond yields. The two have generally traded together, rising during periods of economic growth and falling during periods of contraction. Consider the period from 1998 through 2010, during which the U.S. economy experienced two expansions as well as two recessions: Then central banks came to the rescue. Fed Chairman Ben Bernanke led from Washington with the help of the bank''s current $3.6T balance sheet. He''s accompanied by Mario Draghi at the European Central Bank and an equally forthright Shinzo Abe in Japan. Their coordinated monetary expansion has provided all the sugar needed for an equities moonshot, while they vowed to hold global borrowing costs at record lows']}))\nz.show(esa_wiki_mod.transform(temp_pd))", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:57:11+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "FEATURE_ID": "string", - "VALUE": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "FEATURE_ID\tVALUE\nMario Draghi\t0.24037576171299804\nBen Bernanke\t0.2221630541966304\nGroup of Thirty\t0.18669094628819033\nBank of Japan\t0.11759596635595797\nEconomy of Japan\t0.10723760682465146\nMonetary reform\t0.09989730358984214\nGreat Depression\t0.09815980234207439\nMoney supply\t0.09810361381368604\nAbenomics\t0.0978167373126341\nBank of Canada\t0.09528206234753946\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_-1597925021", - "id": "20220729-215332_734714447", - "dateCreated": "2021-02-18T05:44:42+0000", - "dateStarted": "2022-07-29T21:57:11+0000", - "dateFinished": "2022-07-29T21:57:12+0000", - "status": "FINISHED", - "$$hashKey": "object:55" - }, - { - "text": "%md\n# Comparing Strings for Similarity of Text using the Wikipedia Model\n---", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:57:12+0000", - "progress": 0, - "config": { - "tableHide": false, - "editorSetting": { - "language": "md", - "editOnDblClick": false, - "completionSupport": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Comparing Strings for Similarity of Text using the Wikipedia Model

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The mission is an unprecedented attempt to find signs of past microbial life at the site of an ancient martian river, delta and lakebed. Mission managers at NASA Jet Propulsion Laboratory in Pasadena, California, said Wednesday that the spacecraft, still attached to its interplanetary cruise stage, is healthy and flawlessly executing its final approach to Jezero Crater.',\n 'NASA has selected SpaceX to deliver the first two segments of the moon-orbiting Gateway space station for its upcoming Artemis program, which aims to put astronauts back on the moon. The elements will launch atop a Falcon Heavy rocket, sometime in 2024. The flight, which is the second to be awarded to SpaceX this week will carry the Gateway''s power and habitation modules. Once deposited in lunar orbit, the Gateway will serve as an outpost for astronauts and equipment heading to the moon as part of NASA Artemis program. Roughly one-sixth the size of the International Space Station, the Gateway will support research investigations, crew, and expeditions to the lunar surface.']}))\nz.show(esa_wiki_mod.feature_compare(temp_pd,\n compare_cols = ['TEXT']))\n ", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:57:15+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false, - "completionKey": "TAB", - "completionSupport": true - }, - "colWidth": 6, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "editorHide": false, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 84.1667, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "SIMILARITY": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "SIMILARITY\n0.4868245114801608\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_-175417344", - "id": "20220729-215332_45424930", - "dateCreated": "2021-02-18T06:05:03+0000", - "dateStarted": "2022-07-29T21:57:15+0000", - "dateFinished": "2022-07-29T21:57:16+0000", - "status": "FINISHED", - "$$hashKey": "object:61" - }, - { - "title": "News on Nasa Rover and Tennis Naomi Osaka using ESA Wikipedia model", - "text": "%python\n\ntemp_pd = oml.push(pd.DataFrame({'TEXT':['NASA Perseverance Mars rover closed in on the red planet after a journey of 293 million miles, hurtling toward a nail-biting seven-minute descent to touchdown Thursday. The mission is an unprecedented attempt to find signs of past microbial life at the site of an ancient martian river, delta and lakebed. Mission managers at NASA Jet Propulsion Laboratory in Pasadena, California, said Wednesday that the spacecraft, still attached to its interplanetary cruise stage, is healthy and flawlessly executing its final approach to Jezero Crater.',\n 'Naomi Osaka, who hasnt lost an official match since last February, put together a dominating performance in the Australian Open semifinals, beating Williams 6-3, 6-4 and ending hopes that the 39-year old American would tie Margaret Court all-time Slam record at this tournament. Osaka, seeking her fourth major title and second Australian Open championship, will play the winner of the second semifinal between American Jennifer Brady, the No. 22 seed, and No. 25 seed Karolina Muchova.']}))\nz.show(esa_wiki_mod.feature_compare(temp_pd,\n compare_cols = ['TEXT']))\n ", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:57:16+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false, - "completionKey": "TAB", - "completionSupport": true - }, - "colWidth": 6, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "editorHide": false, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 84.1667, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "SIMILARITY": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "SIMILARITY\n0.03987043350098296\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659131612714_-125479958", - "id": "20220729-215332_108692970", - "dateCreated": "2021-02-18T06:13:34+0000", - "dateStarted": "2022-07-29T21:57:16+0000", - "dateFinished": "2022-07-29T21:57:16+0000", - "status": "FINISHED", - "$$hashKey": "object:62" - }, - { - "text": "%md\n---\n# End of Script\n---", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T21:57:16+0000", - "progress": 0, - "config": { - "tableHide": false, - "editorSetting": { - "language": "md", - "editOnDblClick": false, - "completionSupport": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "
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Explicit Semantic Analysis (ESA) for Text Analytics

\n

Explicit Semantic Analysis (ESA) is an unsupervised algorithm for feature extraction of explicit features based on an existing knowledge base. It is the process of understanding the meaning of a section of text as a combination of the concepts found in the text. Compared to other techniques such as Latent Dirichlet Association (LDA) or Term Frequency-Inverse Document Frequency (TF-IDF), ESA offers some unique benefits. Most notably, it improves text document categorization by calculating semantic relatedness (how similar in meaning two words or pieces of text are to each other) between the documents and a set of topics that are explicitly defined and described by humans.

\n

The Oracle Machine Learning for Python function oml.esa extracts text-based features from a corpus of documents and performs document similarity comparisons. All processing occurs inside Oracle Autonomous Database.

\n

In this notebook, we cover the basic usage of ESA, where we extract topics from the comments provided.

\n\n

Copyright (c) 2021 Oracle Corporation

\n
The Universal Permissive License (UPL), Version 1.0
\n
\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_-2106770621", - "id": "20220729-182949_439696071", - "dateCreated": "2021-07-14T19:09:02+0000", - "dateStarted": "2022-07-29T19:25:26+0000", - "dateFinished": "2022-07-29T19:25:28+0000", - "status": "FINISHED", - "focus": true, - "$$hashKey": "object:41" - }, - { - "title": "For more information...", - "text": "%md\n\nOracle ADW Documentation https://docs.oracle.com/en/cloud/paas/autonomous-data-warehouse-cloud/index.html\nOML folder on Oracle Github : https://github.com/oracle/oracle-db-examples/tree/master/machine-learning\nOML web page: https://www.oracle.com/machine-learning\nOML Explicit Semantic Analysis: https://www.oracle.com/goto/ml-explicit-semantic-analysis", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:28+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Oracle ADW Documentation https://docs.oracle.com/en/cloud/paas/autonomous-data-warehouse-cloud/index.html\n
OML folder on Oracle Github : https://github.com/oracle/oracle-db-examples/tree/master/machine-learning\n
OML web page: https://www.oracle.com/machine-learning\n
OML Explicit Semantic Analysis: https://www.oracle.com/goto/ml-explicit-semantic-analysis

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_1836003831", - "id": "20220729-182949_1274384067", - "dateCreated": "2021-07-14T19:49:58+0000", - "dateStarted": "2022-07-29T19:25:28+0000", - "dateFinished": "2022-07-29T19:25:28+0000", - "status": "FINISHED", - "$$hashKey": "object:42" - }, - { - "title": "Import libraries", - "text": "%python\n\nimport oml\nimport pandas as pd", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:28+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "editorHide": false, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_1247749151", - "id": "20220729-182949_46129540", - "dateCreated": "2021-07-14T19:18:52+0000", - "dateStarted": "2022-07-29T19:25:28+0000", - "dateFinished": "2022-07-29T19:25:38+0000", - "status": "FINISHED", - "$$hashKey": "object:44" - }, - { - "title": "Create test and training data", - "text": "%python\n\ndat = oml.push(pd.DataFrame(\n {'COMMENTS':['Aids in Africa: Planning for a long war',\n 'Mars rover maneuvers for rim shot',\n 'Mars express confirms presence of water at Mars south pole',\n 'NASA announces major Mars rover finding',\n 'Drug access, Asia threat in focus at AIDS summit',\n 'NASA Mars Odyssey THEMIS image: typical crater',\n 'Road blocks for Aids'],\n 'ID':[1,2,3,4,5,6,7]})).split(ratio=(0.7,0.3), seed = 1234)\n\ntrain_dat = dat[0]\ntest_dat = dat[1]\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:38+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_2007659148", - "id": "20220729-182949_892632070", - "dateCreated": "2021-07-14T19:56:36+0000", - "dateStarted": "2022-07-29T19:25:38+0000", - "dateFinished": "2022-07-29T19:25:39+0000", - "status": "FINISHED", - "$$hashKey": "object:45" - }, - { - "title": "Check the test data", - "text": "%python\n\nz.show(test_dat)\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:39+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "COMMENTS": "string", - "ID": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "COMMENTS\tID\nAids in Africa: Planning for a long war\t1\nNASA announces major Mars rover finding\t4\nRoad blocks for Aids\t7\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_1667536839", - "id": "20220729-182949_107256677", - "dateCreated": "2021-07-15T16:35:22+0000", - "dateStarted": "2022-07-29T19:25:39+0000", - "dateFinished": "2022-07-29T19:25:39+0000", - "status": "FINISHED", - "$$hashKey": "object:46" - }, - { - "title": "Check the training data", - "text": "%python\n\nz.show(train_dat)", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:39+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "COMMENTS": "string", - "ID": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "COMMENTS\tID\nMars rover maneuvers for rim shot\t2\nMars express confirms presence of water at Mars south pole\t3\nDrug access, Asia threat in focus at AIDS summit\t5\nNASA Mars Odyssey THEMIS image: typical crater\t6\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_690735834", - "id": "20220729-182949_1627430652", - "dateCreated": "2021-07-15T16:35:47+0000", - "dateStarted": "2022-07-29T19:25:40+0000", - "dateFinished": "2022-07-29T19:25:40+0000", - "status": "FINISHED", - "$$hashKey": "object:47" - }, - { - "title": "Create a policy for text indexing", - "text": "%script\n\n-- Drop the policy if it exists\nBEGIN ctx_ddl.drop_policy('ESA_TXT_POLICY'); \nexception when others then NULL;\n END;\n\nBEGIN ctx_ddl.create_policy('ESA_TXT_POLICY'); \nexception when others then NULL;\n END;", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:40+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "plsql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/plsql", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TEXT", - "data": "\nPL/SQL procedure successfully completed.\n\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_-1320201853", - "id": "20220729-182949_474931353", - "dateCreated": "2021-07-14T20:00:24+0000", - "dateStarted": "2022-07-29T19:25:40+0000", - "dateFinished": "2022-07-29T19:25:45+0000", - "status": "FINISHED", - "$$hashKey": "object:48" - }, - { - "title": "Specify model settings", - "text": "%python\n\nodm_settings = {'odms_text_policy_name': 'ESA_TXT_POLICY',\n '\"ODMS_TEXT_MIN_DOCUMENTS\"': 1,\n '\"ESAS_MIN_ITEMS\"': 1}\n\nctx_settings = {'COMMENTS':\n 'TEXT(POLICY_NAME:ESA_TXT_POLICY)(TOKEN_TYPE:STEM)'}\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:45+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_-335666475", - "id": "20220729-182949_168586074", - "dateCreated": "2021-07-14T20:02:51+0000", - "dateStarted": "2022-07-29T19:25:45+0000", - "dateFinished": "2022-07-29T19:25:45+0000", - "status": "FINISHED", - "$$hashKey": "object:49" - }, - { - "title": "Create an ESA model object ", - "text": "%python\n\n# Delete if ESA model exists\ntry:\n oml.drop(model = 'ESA_MOD')\nexcept:\n print('No such model')\n \nesa_mod = oml.esa(**odm_settings)", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:45+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TEXT", - "data": "No such model\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_1384073227", - "id": "20220729-182949_672229069", - "dateCreated": "2021-07-14T20:04:40+0000", - "dateStarted": "2022-07-29T19:25:45+0000", - "dateFinished": "2022-07-29T19:25:45+0000", - "status": "FINISHED", - "$$hashKey": "object:50" - }, - { - "title": "View the model settings", - "text": "%python\n\nesa_mod.settings", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:46+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TEXT", - "data": "{'odms_text_policy_name': 'ESA_TXT_POLICY', '\"odms_text_min_documents\"': 1, '\"esas_min_items\"': 1}\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_-961290906", - "id": "20220729-182949_1300494925", - "dateCreated": "2021-07-14T22:26:01+0000", - "dateStarted": "2022-07-29T19:25:46+0000", - "dateFinished": "2022-07-29T19:25:46+0000", - "status": "FINISHED", - "$$hashKey": "object:51" - }, - { - "title": " Fit the model according to the training data and parameter settings", - "text": "%python\n\nesa_mod = esa_mod.fit(train_dat, case_id='ID', ctx_settings = ctx_settings)", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:46+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_2028540298", - "id": "20220729-182949_639795532", - "dateCreated": "2021-07-14T20:06:17+0000", - "dateStarted": "2022-07-29T19:25:46+0000", - "dateFinished": "2022-07-29T19:25:47+0000", - "status": "FINISHED", - "$$hashKey": "object:52" - }, - { - "title": "Show the model details", - "text": "%python\n\nesa_mod", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:47+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TEXT", - "data": "\nAlgorithm Name: Explicit Semantic Analysis\n\nMining Function: FEATURE_EXTRACTION\n\nSettings: \n setting name setting value\n0 ALGO_NAME ALGO_EXPLICIT_SEMANTIC_ANALYS\n1 ESAS_MIN_ITEMS 1\n2 ESAS_TOPN_FEATURES 1000\n3 ESAS_VALUE_THRESHOLD .00000001\n4 ODMS_DETAILS ODMS_ENABLE\n5 ODMS_MISSING_VALUE_TREATMENT ODMS_MISSING_VALUE_AUTO\n6 ODMS_SAMPLING ODMS_SAMPLING_DISABLE\n7 ODMS_TEXT_MAX_FEATURES 300000\n8 ODMS_TEXT_MIN_DOCUMENTS 1\n9 ODMS_TEXT_POLICY_NAME ESA_TXT_POLICY\n10 PREP_AUTO ON\n\nGlobal Statistics: \n attribute name attribute value\n0 NUM_ROWS 4\n\nAttributes: \nCOMMENTS\n\nPartition: NO\n\nFeatures: \n\n FEATURE_ID ATTRIBUTE_NAME ATTRIBUTE_VALUE COEFFICIENT\n0 2 COMMENTS.MANEUVERS None 0.497330\n1 2 COMMENTS.MARS None 0.103205\n2 2 COMMENTS.RIM None 0.497330\n3 2 COMMENTS.ROVER None 0.497330\n4 2 COMMENTS.SHOT None 0.497330\n5 3 COMMENTS.CONFIRMS None 0.404991\n6 3 COMMENTS.EXPRESS None 0.404991\n7 3 COMMENTS.MARS None 0.126065\n8 3 COMMENTS.POLE None 0.404991\n9 3 COMMENTS.PRESENCE None 0.404991\n10 3 COMMENTS.SOUTH None 0.404991\n11 3 COMMENTS.WATER None 0.404991\n12 5 COMMENTS.ACCESS None 0.377964\n13 5 COMMENTS.AIDS None 0.377964\n14 5 COMMENTS.ASIA None 0.377964\n15 5 COMMENTS.DRUG None 0.377964\n16 5 COMMENTS.FOCUS None 0.377964\n17 5 COMMENTS.SUMMIT None 0.377964\n18 5 COMMENTS.THREAT None 0.377964\n19 6 COMMENTS.CRATER None 0.406791\n20 6 COMMENTS.IMAGE None 0.406791\n21 6 COMMENTS.MARS None 0.084417\n22 6 COMMENTS.NASA None 0.406791\n23 6 COMMENTS.ODYSSEY None 0.406791\n24 6 COMMENTS.THEMIS None 0.406791\n25 6 COMMENTS.TYPICAL None 0.406791\n\n\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_-1528865936", - "id": "20220729-182949_1327327337", - "dateCreated": "2021-07-26T16:37:05+0000", - "dateStarted": "2022-07-29T19:25:48+0000", - "dateFinished": "2022-07-29T19:25:48+0000", - "status": "FINISHED", - "$$hashKey": "object:53" - }, - { - "title": "Show the model details for each feature", - "text": "%python\n\nz.show(esa_mod.features.round(4))\n\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:48+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "editorHide": false, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "FEATURE_ID": "string", - "ATTRIBUTE_NAME": "string", - "ATTRIBUTE_VALUE": "string", - "COEFFICIENT": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "FEATURE_ID\tATTRIBUTE_NAME\tATTRIBUTE_VALUE\tCOEFFICIENT\n2\tCOMMENTS.MANEUVERS\tNone\t0.4973\n2\tCOMMENTS.MARS\tNone\t0.1032\n2\tCOMMENTS.RIM\tNone\t0.4973\n2\tCOMMENTS.ROVER\tNone\t0.4973\n2\tCOMMENTS.SHOT\tNone\t0.4973\n3\tCOMMENTS.CONFIRMS\tNone\t0.405\n3\tCOMMENTS.EXPRESS\tNone\t0.405\n3\tCOMMENTS.MARS\tNone\t0.1261\n3\tCOMMENTS.POLE\tNone\t0.405\n3\tCOMMENTS.PRESENCE\tNone\t0.405\n3\tCOMMENTS.SOUTH\tNone\t0.405\n3\tCOMMENTS.WATER\tNone\t0.405\n5\tCOMMENTS.ACCESS\tNone\t0.378\n5\tCOMMENTS.AIDS\tNone\t0.378\n5\tCOMMENTS.ASIA\tNone\t0.378\n5\tCOMMENTS.DRUG\tNone\t0.378\n5\tCOMMENTS.FOCUS\tNone\t0.378\n5\tCOMMENTS.SUMMIT\tNone\t0.378\n5\tCOMMENTS.THREAT\tNone\t0.378\n6\tCOMMENTS.CRATER\tNone\t0.4068\n6\tCOMMENTS.IMAGE\tNone\t0.4068\n6\tCOMMENTS.MARS\tNone\t0.0844\n6\tCOMMENTS.NASA\tNone\t0.4068\n6\tCOMMENTS.ODYSSEY\tNone\t0.4068\n6\tCOMMENTS.THEMIS\tNone\t0.4068\n6\tCOMMENTS.TYPICAL\tNone\t0.4068\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_-332203672", - "id": "20220729-182949_1813596233", - "dateCreated": "2021-07-14T20:07:01+0000", - "dateStarted": "2022-07-29T19:25:48+0000", - "dateFinished": "2022-07-29T19:25:48+0000", - "status": "FINISHED", - "$$hashKey": "object:54" - }, - { - "title": "Predicted top 2 features", - "text": "%python\n\nz.show(esa_mod.transform(test_dat, \n supplemental_cols = test_dat[:, ['ID', 'COMMENTS']], \n topN = 2).sort_values(by = ['ID']).round(4))\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:48+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "ID": "string", - "COMMENTS": "string", - "TOP_1": "string", - "TOP_1_VAL": "string", - "TOP_2": "string", - "TOP_2_VAL": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "ID\tCOMMENTS\tTOP_1\tTOP_1_VAL\tTOP_2\tTOP_2_VAL\n1\tAids in Africa: Planning for a long war\t5\t1.0\tnan\tnan\n4\tNASA announces major Mars rover finding\t2\t0.7738\t6.0\t0.6329\n7\tRoad blocks for Aids\t5\t1.0\tnan\tnan\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_-919449389", - "id": "20220729-182949_1050314261", - "dateCreated": "2021-07-15T21:13:53+0000", - "dateStarted": "2022-07-29T19:25:48+0000", - "dateFinished": "2022-07-29T19:25:49+0000", - "status": "FINISHED", - "$$hashKey": "object:55" - }, - { - "title": "View the model name internal to the database", - "text": "%sql\n\nSELECT * from all_mining_models WHERE ALGORITHM='EXPLICIT_SEMANTIC_ANALYS'", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:49+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "OWNER": "string", - "MODEL_NAME": "string", - "MINING_FUNCTION": "string", - "ALGORITHM": "string", - "ALGORITHM_TYPE": "string", - "CREATION_DATE": "string", - "BUILD_DURATION": "string", - "MODEL_SIZE": "string", - "PARTITIONED": "string", - "COMMENTS": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "OWNER\tMODEL_NAME\tMINING_FUNCTION\tALGORITHM\tALGORITHM_TYPE\tCREATION_DATE\tBUILD_DURATION\tMODEL_SIZE\tPARTITIONED\tCOMMENTS\nOMLUSER\tOPE$DM3246_146_00072\tFEATURE_EXTRACTION\tEXPLICIT_SEMANTIC_ANALYS\tNATIVE\t2022-07-29 19:25:46\t\t0\tNO\t\nOMLUSER\tWIKI_MODEL\tFEATURE_EXTRACTION\tEXPLICIT_SEMANTIC_ANALYS\tNATIVE\t2022-07-29 16:32:50\t0\t0\tNO\t\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_-566413779", - "id": "20220729-182949_209737835", - "dateCreated": "2021-07-14T21:17:45+0000", - "dateStarted": "2022-07-29T19:25:49+0000", - "dateFinished": "2022-07-29T19:25:49+0000", - "status": "FINISHED", - "$$hashKey": "object:56" - }, - { - "title": "Rename the model in the database", - "text": "%python\n\nesa_mod.model_name='ESA_MOD'", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:49+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_10340114", - "id": "20220729-182949_679098290", - "dateCreated": "2021-07-14T21:42:35+0000", - "dateStarted": "2022-07-29T19:25:49+0000", - "dateFinished": "2022-07-29T19:25:50+0000", - "status": "FINISHED", - "$$hashKey": "object:57" - }, - { - "title": "View new model name in the database", - "text": "%sql\n\nselect * from USER_MINING_MODELS where model_name='ESA_MOD'", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:50+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "MODEL_NAME": "string", - "MINING_FUNCTION": "string", - "ALGORITHM": "string", - "ALGORITHM_TYPE": "string", - "CREATION_DATE": "string", - "BUILD_DURATION": "string", - "MODEL_SIZE": "string", - "PARTITIONED": "string", - "COMMENTS": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "MODEL_NAME\tMINING_FUNCTION\tALGORITHM\tALGORITHM_TYPE\tCREATION_DATE\tBUILD_DURATION\tMODEL_SIZE\tPARTITIONED\tCOMMENTS\nESA_MOD\tFEATURE_EXTRACTION\tEXPLICIT_SEMANTIC_ANALYS\tNATIVE\t2022-07-29 19:25:46\t\t0\tNO\t\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_-2047008806", - "id": "20220729-182949_243755508", - "dateCreated": "2021-07-14T21:34:59+0000", - "dateStarted": "2022-07-29T19:25:50+0000", - "dateFinished": "2022-07-29T19:25:50+0000", - "status": "FINISHED", - "$$hashKey": "object:58" - }, - { - "title": "View renamed model in Python", - "text": "%python\n\noml.esa(model_name = 'ESA_MOD') ", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:50+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TEXT", - "data": "\nModel Name: ESA_MOD\n\nModel Owner: OMLUSER\n\nAlgorithm Name: Explicit Semantic Analysis\n\nMining Function: FEATURE_EXTRACTION\n\nSettings: \n setting name setting value\n0 ALGO_NAME ALGO_EXPLICIT_SEMANTIC_ANALYS\n1 ESAS_MIN_ITEMS 1\n2 ESAS_TOPN_FEATURES 1000\n3 ESAS_VALUE_THRESHOLD .00000001\n4 ODMS_DETAILS ODMS_ENABLE\n5 ODMS_MISSING_VALUE_TREATMENT ODMS_MISSING_VALUE_AUTO\n6 ODMS_SAMPLING ODMS_SAMPLING_DISABLE\n7 ODMS_TEXT_MAX_FEATURES 300000\n8 ODMS_TEXT_MIN_DOCUMENTS 1\n9 ODMS_TEXT_POLICY_NAME ESA_TXT_POLICY\n10 PREP_AUTO ON\n\nGlobal Statistics: \n attribute name attribute value\n0 NUM_ROWS 4\n\nAttributes: \nCOMMENTS\n\nPartition: NO\n\nFeatures: \n\n FEATURE_ID ATTRIBUTE_NAME ATTRIBUTE_VALUE COEFFICIENT\n0 2 COMMENTS.MANEUVERS None 0.497330\n1 2 COMMENTS.MARS None 0.103205\n2 2 COMMENTS.RIM None 0.497330\n3 2 COMMENTS.ROVER None 0.497330\n4 2 COMMENTS.SHOT None 0.497330\n5 3 COMMENTS.CONFIRMS None 0.404991\n6 3 COMMENTS.EXPRESS None 0.404991\n7 3 COMMENTS.MARS None 0.126065\n8 3 COMMENTS.POLE None 0.404991\n9 3 COMMENTS.PRESENCE None 0.404991\n10 3 COMMENTS.SOUTH None 0.404991\n11 3 COMMENTS.WATER None 0.404991\n12 5 COMMENTS.ACCESS None 0.377964\n13 5 COMMENTS.AIDS None 0.377964\n14 5 COMMENTS.ASIA None 0.377964\n15 5 COMMENTS.DRUG None 0.377964\n16 5 COMMENTS.FOCUS None 0.377964\n17 5 COMMENTS.SUMMIT None 0.377964\n18 5 COMMENTS.THREAT None 0.377964\n19 6 COMMENTS.CRATER None 0.406791\n20 6 COMMENTS.IMAGE None 0.406791\n21 6 COMMENTS.MARS None 0.084417\n22 6 COMMENTS.NASA None 0.406791\n23 6 COMMENTS.ODYSSEY None 0.406791\n24 6 COMMENTS.THEMIS None 0.406791\n25 6 COMMENTS.TYPICAL None 0.406791\n\n\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_-1703910118", - "id": "20220729-182949_1682439199", - "dateCreated": "2021-07-14T21:36:16+0000", - "dateStarted": "2022-07-29T19:25:50+0000", - "dateFinished": "2022-07-29T19:25:51+0000", - "status": "FINISHED", - "$$hashKey": "object:59" - }, - { - "title": "Make predictions on the test data", - "text": "%python\n\nesa_pred = esa_mod.predict(test_dat, supplemental_cols = test_dat[:, ['ID', 'COMMENTS']])\nz.show(esa_pred)\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:51+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "ID": "string", - "COMMENTS": "string", - "FEATURE_ID": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "ID\tCOMMENTS\tFEATURE_ID\n1\tAids in Africa: Planning for a long war\t5\n4\tNASA announces major Mars rover finding\t2\n7\tRoad blocks for Aids\t5\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_1358274903", - "id": "20220729-182949_1787470844", - "dateCreated": "2021-07-14T20:07:43+0000", - "dateStarted": "2022-07-29T19:25:51+0000", - "dateFinished": "2022-07-29T19:25:51+0000", - "status": "FINISHED", - "$$hashKey": "object:60" - }, - { - "title": "Change the settings and refit the model", - "text": "%python\n\nnew_setting = {'ESAS_VALUE_THRESHOLD': '0.01',\n 'ODMS_TEXT_MAX_FEATURES': '2',\n 'FEAT_NUM_FEATURES': '2',\n 'ESAS_TOPN_FEATURES': '2'}\n ", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:51+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_916229952", - "id": "20220729-182949_330616504", - "dateCreated": "2021-07-14T20:09:33+0000", - "dateStarted": "2022-07-29T19:25:51+0000", - "dateFinished": "2022-07-29T19:25:51+0000", - "status": "FINISHED", - "$$hashKey": "object:61" - }, - { - "title": "Refit the model with new settings - 2 features maximum ", - "text": "%python\n\n# Delete if ESA model exists\ntry:\n oml.drop(model = 'ESA_MOD_2')\nexcept:\n print('No such model')\n \nesa_mod.set_params(**new_setting).fit(train_dat, case_id = 'ID', \n ctx_settings = ctx_settings,\n model_name='ESA_MOD_2')\n\nz.show(esa_mod.feature_compare(test_dat,\n compare_cols = ['COMMENTS'],\n supplemental_cols = ['COMMENTS']))", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:51+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "COMMENTS_A": "string", - "COMMENTS_B": "string", - "SIMILARITY": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - }, - "1": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "COMMENTS_A": "string", - "COMMENTS_B": "string", - "SIMILARITY": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TEXT", - "data": "No such model\n" - }, - { - "type": "TABLE", - "data": "COMMENTS_A\tCOMMENTS_B\tSIMILARITY\nAids in Africa: Planning for a long war\tNASA announces major Mars rover finding\t0.0\nAids in Africa: Planning for a long war\tRoad blocks for Aids\t1.0\nNASA announces major Mars rover finding\tRoad blocks for Aids\t0.0\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_1484041688", - "id": "20220729-182949_650763763", - "dateCreated": "2021-07-15T21:22:17+0000", - "dateStarted": "2022-07-29T19:25:52+0000", - "dateFinished": "2022-07-29T19:25:53+0000", - "status": "FINISHED", - "$$hashKey": "object:62" - }, - { - "title": "List ESA model views", - "text": "%sql\n\nSELECT view_name, view_type FROM user_mining_model_views\nWHERE model_name='ESA_MOD_2'\nORDER BY view_name;\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:53+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "VIEW_NAME": "string", - "VIEW_TYPE": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "VIEW_NAME\tVIEW_TYPE\nDM$VAESA_MOD_2\tExplicit Semantic Analysis Matrix\nDM$VFESA_MOD_2\tExplicit Semantic Analysis Features\nDM$VGESA_MOD_2\tGlobal Name-Value Pairs\nDM$VNESA_MOD_2\tNormalization and Missing Value Handling\nDM$VSESA_MOD_2\tComputed Settings\nDM$VWESA_MOD_2\tModel Build Alerts\nDM$VXESA_MOD_2\tText Features\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_-853371444", - "id": "20220729-182949_2109045297", - "dateCreated": "2021-07-15T17:17:36+0000", - "dateStarted": "2022-07-29T19:25:53+0000", - "dateFinished": "2022-07-29T19:25:53+0000", - "status": "FINISHED", - "$$hashKey": "object:63" - }, - { - "title": "The VA view shows associations among features (topics) and words", - "text": "%md\n\n*ATTRIBUTE_SUBNAME* refers to words, or tokens. The strength of the associations is measured by *COEFFICIENT*. Higher coefficient values indicate a stronger association.\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:53+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

ATTRIBUTE_SUBNAME refers to words, or tokens. The strength of the associations is measured by COEFFICIENT. Higher coefficient values indicate a stronger association.

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_-757810283", - "id": "20220729-182949_1109373752", - "dateCreated": "2021-07-15T19:51:19+0000", - "dateStarted": "2022-07-29T19:25:53+0000", - "dateFinished": "2022-07-29T19:25:53+0000", - "status": "FINISHED", - "$$hashKey": "object:64" - }, - { - "title": "", - "text": "%sql\n\nSELECT * from dm$vaesa_mod_2", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:53+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "title": false, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "PARTITION_NAME": "string", - "FEATURE_ID": "string", - "ATTRIBUTE_NAME": "string", - "ATTRIBUTE_SUBNAME": "string", - "ATTRIBUTE_VALUE": "string", - "COEFFICIENT": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "PARTITION_NAME\tFEATURE_ID\tATTRIBUTE_NAME\tATTRIBUTE_SUBNAME\tATTRIBUTE_VALUE\tCOEFFICIENT\n\t5\tCOMMENTS\tACCESS\t\t0.3779644730092272\n\t5\tCOMMENTS\tAIDS\t\t0.3779644730092272\n\t5\tCOMMENTS\tASIA\t\t0.3779644730092272\n\t3\tCOMMENTS\tCONFIRMS\t\t0.4049912817146355\n\t6\tCOMMENTS\tCRATER\t\t0.4067910617987843\n\t5\tCOMMENTS\tDRUG\t\t0.3779644730092272\n\t3\tCOMMENTS\tEXPRESS\t\t0.4049912817146355\n\t5\tCOMMENTS\tFOCUS\t\t0.3779644730092272\n\t6\tCOMMENTS\tIMAGE\t\t0.4067910617987843\n\t2\tCOMMENTS\tMANEUVERS\t\t0.4973300370260457\n\t2\tCOMMENTS\tMARS\t\t0.10320531520560347\n\t3\tCOMMENTS\tMARS\t\t0.12606494521008016\n\t6\tCOMMENTS\tNASA\t\t0.4067910617987843\n\t6\tCOMMENTS\tODYSSEY\t\t0.4067910617987843\n\t3\tCOMMENTS\tPOLE\t\t0.4049912817146355\n\t3\tCOMMENTS\tPRESENCE\t\t0.4049912817146355\n\t2\tCOMMENTS\tRIM\t\t0.4973300370260457\n\t2\tCOMMENTS\tROVER\t\t0.4973300370260457\n\t2\tCOMMENTS\tSHOT\t\t0.4973300370260457\n\t3\tCOMMENTS\tSOUTH\t\t0.4049912817146355\n\t5\tCOMMENTS\tSUMMIT\t\t0.3779644730092272\n\t6\tCOMMENTS\tTHEMIS\t\t0.4067910617987843\n\t5\tCOMMENTS\tTHREAT\t\t0.3779644730092272\n\t6\tCOMMENTS\tTYPICAL\t\t0.4067910617987843\n\t3\tCOMMENTS\tWATER\t\t0.4049912817146355\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_-281939024", - "id": "20220729-182949_2011915469", - "dateCreated": "2021-07-15T16:44:39+0000", - "dateStarted": "2022-07-29T19:25:54+0000", - "dateFinished": "2022-07-29T19:25:54+0000", - "status": "FINISHED", - "$$hashKey": "object:65" - }, - { - "title": "Show the associations for selected words", - "text": "%sql\n\nSELECT ATTRIBUTE_SUBNAME, count(ATTRIBUTE_SUBNAME) FROM dm$vaesa_mod_2\nWHERE ATTRIBUTE_SUBNAME='MARS'\nGROUP BY ATTRIBUTE_SUBNAME\n\n\n\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:54+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "ATTRIBUTE_SUBNAME": "string", - "COUNT(ATTRIBUTE_SUBNAME)": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "ATTRIBUTE_SUBNAME\tCOUNT(ATTRIBUTE_SUBNAME)\nMARS\t2\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_-1595183987", - "id": "20220729-182949_530913670", - "dateCreated": "2021-07-15T16:48:28+0000", - "dateStarted": "2022-07-29T19:25:54+0000", - "dateFinished": "2022-07-29T19:25:54+0000", - "status": "FINISHED", - "$$hashKey": "object:66" - }, - { - "title": "View the help file for ESA", - "text": "%python\n\nhelp(oml.esa)", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:54+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TEXT", - "data": "Help on class esa in module oml.algo.esa:\n\nclass esa(oml.algo.model.odmModel)\n | esa(model_name=None, model_owner=None, **params)\n | \n | In-database `Explicit Semantic Analysis `_ Model\n | \n | Builds an Explicit Semantic Analysis (ESA) Model to be used for feature extraction. \n | This function exposes the corresponding Oracle Machine Learning in-database algorithm.\n | ESA uses concepts of an existing knowledge base as features rather than latent\n | features derived by latent semantic analysis methods such as Singular\n | Value Decomposition and Latent Dirichlet Allocation. Each row, for example,\n | a document in the training data maps to a feature, that is, a concept.\n | ESA works best with concepts represented by text documents.\n | It has multiple applications in the area of text processing, most\n | notably semantic relatedness (similarity) and explicit topic modeling.\n | Text similarity use cases might involve, for example, resume matching, searching\n | for similar blog postings, and so on.\n | \n | :Attributes:\n | \n | **features** : oml.DataFrame\n | \n | Description of each feature extracted. \n | It includes the following components:\n | \n | - feature_id: The unique identifier of a feature as it appears in the training data\n | - attribute_name: The attribute name\n | - attribute_value: The attribute value\n | - coefficient: The coefficient (weight) associated with the attribute in a particular feature.\n | \n | Method resolution order:\n | esa\n | oml.algo.model.odmModel\n | builtins.object\n | \n | Methods defined here:\n | \n | __init__(self, model_name=None, model_owner=None, **params)\n | Initializes an instance of esa object.\n | \n | Parameters\n | ----------\n | model_name : string or None (default)\n | The name of an existing database Explicit Semantic Analysis model to create an oml.esa object from.\n | The specified database model is not dropped when the oml.esa object is deleted.\n | model_owner: string or None (default)\n | The owner name of the existing Explicit Semantic Analysis model\n | The current database user by default\n | params : key-value pairs or dict\n | Oracle Machine Learning parameter settings. Each list element's name and\n | value refer to the parameter setting name and value, respectively.\n | The setting value must be numeric or string. Refer to `Oracle Data Mining\n | Model Settings `_\n | for applicable parameters and valid values. Global and Automatic Data\n | Preparation Settings in Table 5-5 apply generally to the model.\n | Mining Function Settings for Feature Extraction and `Algorithm-specific\n | Settings `_\n | are applicable to Explicit Semantic Analysis model.\n | \n | __repr__(self)\n | \n | feature_compare(self, x, compare_cols=None, supplemental_cols=None)\n | Compares features of data and generates relatedness.\n | \n | Parameters\n | ----------\n | x : an OML object\n | The data used to measure relatedness.\n | compare_cols : str, a list of str or None (default)\n | The column(s) used to measure data relatedness.\n | If None, all the columns of ``x`` are compared to measure relatedness.\n | supplemental_cols : a list of str or None (default)\n | A list of columns to display along with the resulting 'SIMILARITY' column.\n | \n | Returns\n | -------\n | pred : oml.DataFrame\n | Contains a 'SIMILARITY' column that measures relatedness and supplementary columns if specified.\n | \n | fit(self, x, model_name=None, case_id=None, ctx_settings=None)\n | Fits an ESA Model according to the training data and parameter settings.\n | \n | Parameters\n | ----------\n | x : an OML object\n | Attribute values for building the model.\n | model_name : string or None (default)\n | User-specified model name.\n | The user-specified database model is not dropped when oml.esa object is deleted.\n | If None, a system-generated model name will be used.\n | The system-generated model is dropped when oml.esa object is deleted\n | unless oml.esa object is saved into a datastore.\n | case_id : string or None (default)\n | The column name used as case id for building the model.\n | ctx_settings : dict or None (default)\n | A list to specify Oracle Text attribute-specific settings.\n | This argument is applicable to building models in Oracle Database 12.2 or later.\n | The name of each list element refers to the text column while the list value\n | is a scalar string specifying the attribute-specific text transformation.\n | The valid entries in the string include TEXT, POLICY_NAME, TOKEN_TYPE, and\n | MAX_FEATURES.\n | \n | predict(self, x, supplemental_cols=None, topN_attrs=False)\n | Makes predictions on new data.\n | \n | Parameters\n | ----------\n | x : an OML object\n | Attribute values used by the model to generate scores.\n | supplemental_cols : oml.DataFrame, oml.Float, oml.String, or None (default)\n | Data set presented with the prediction result.\n | It must be concatenatable with ``x``.\n | topN_attrs : boolean, positive integer, False (default)\n | Returns the top N most important features with the corresponding weights.\n | N is equal to the specified positive integer or 5 if topN_attrs is True.\n | \n | Returns\n | -------\n | pred : oml.DataFrame\n | Contains the features specified by ``supplemental_cols`` and the\n | results. The results include the most likely feature and its probability.\n | \n | transform(self, x, supplemental_cols=None, topN=None)\n | Make predictions and return relevancy for each feature on new data.\n | \n | Parameters\n | ----------\n | x : an OML object\n | Attribute values used by the model to generate scores.\n | supplemental_cols : oml.DataFrame, oml.Float, oml.String, or None (default)\n | Data set presented with the prediction result.\n | It must be concatenatable with ``x``.\n | topN : positive integer or None (default)\n | A positive integer that restricts the returned values to\n | the specified number of features that have the highest topN values.\n | \n | Returns\n | -------\n | pred : oml.DataFrame\n | Contains the relevancy for each feature on new data and the specified ``supplemental_cols``.\n | \n | ----------------------------------------------------------------------\n | Methods inherited from oml.algo.model.odmModel:\n | \n | export_sermodel(self, table=None, partition=None)\n | Export model.\n | \n | Parameters\n | ----------\n | table : string or None (default)\n | A name for the new table where the serialized model is saved.\n | If None, the serialized model will be saved to a temporary table.\n | partition : string or None (default)\n | Name of the partition that needs to be exported.\n | If partition is None, all partitions are exported\n | \n | Returns\n | -------\n | oml_bytes : an oml.Bytes object\n | Contains the BLOB content from the model export\n | \n | get_params(self, params=None, deep=False)\n | Fetches parameters of the model.\n | \n | Parameters\n | ----------\n | params : iterable of strings, None (default)\n | Names of parameters to fetch. If ``params`` is None,\n | fetches all settings.\n | deep : boolean, False (default)\n | Includes the computed and default parameters or not.\n | \n | Returns\n | -------\n | settings : dict mapping str to str\n | \n | set_params(self, **params)\n | Changes parameters of the model.\n | \n | Parameters\n | ----------\n | params : dict object mapping str to str\n | The key should be the name of the setting, and the value should be\n | the new setting.\n | \n | Returns\n | -------\n | model : the model itself.\n | \n | ----------------------------------------------------------------------\n | Readonly properties inherited from oml.algo.model.odmModel:\n | \n | model_owner\n | The owner name of database mining model\n | \n | ----------------------------------------------------------------------\n | Data descriptors inherited from oml.algo.model.odmModel:\n | \n | __dict__\n | dictionary for instance variables (if defined)\n | \n | __weakref__\n | list of weak references to the object (if defined)\n | \n | model_name\n | The given name of database mining model\n | \n | pivot_limit\n | The maximum number of classes, clusters, or features for which the predicted probabilities are presented after pivoted\n\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_-1284188982", - "id": "20220729-182949_1234672817", - "dateCreated": "2021-07-14T22:20:35+0000", - "dateStarted": "2022-07-29T19:25:54+0000", - "dateFinished": "2022-07-29T19:25:54+0000", - "status": "FINISHED", - "$$hashKey": "object:67" - }, - { - "title": "Clean-up", - "text": "%python\n\ntry:\n oml.drop(model = 'ESA_MOD')\nexcept:\n print('No such model')\n\ntry:\n oml.drop(model = 'ESA_MOD_2')\nexcept:\n print('No such model')\n \n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:54+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_-840738613", - "id": "20220729-182949_1982755016", - "dateCreated": "2021-07-15T21:41:00+0000", - "dateStarted": "2022-07-29T19:25:55+0000", - "dateFinished": "2022-07-29T19:25:55+0000", - "status": "FINISHED", - "$$hashKey": "object:68" - }, - { - "text": "%md\n\n---\n# End of Script\n---", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:25:55+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "
\n

End of Script

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\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1659119389831_986661357", - "id": "20220729-182949_1515171788", - "dateCreated": "2021-07-14T21:12:29+0000", - "dateStarted": "2022-07-29T19:25:55+0000", - "dateFinished": "2022-07-29T19:25:55+0000", - "status": "FINISHED", - "$$hashKey": "object:69" - } - ], - "name": "OML4Py Feature Extraction ESA", - "id": "20007", - "defaultInterpreterGroup": "spark", - "noteParams": {}, - "noteForms": {}, - "angularObjects": {}, - "config": { - "looknfeel": "default", - "personalizedMode": "false" - }, - "info": { - "isRunning": false - } -} \ No newline at end of file diff --git a/machine-learning/notebooks/r/OML4Py REST API.json b/machine-learning/notebooks/r/OML4Py REST API.json deleted file mode 100644 index 1a35b4ee..00000000 --- a/machine-learning/notebooks/r/OML4Py REST API.json +++ /dev/null @@ -1,1681 +0,0 @@ -{ - "paragraphs": [ - { - "text": "%md\n\n# OML4Py REST API for invoking embedded R execution\n\nOn Oracle Autonomous Database, OML4Py contains a REST API to run user-defined Python functions saved in the script repository. REST APIs can be called from a web development application, improving the portability of the interface to other types of platforms, increasing project scalability, and allowing components to evolve independently. Use the OML4Py REST API to invoke user-defined Python functions and to list those available in the Python script repository\n\nTo run a script, it must reside in the Python script repository. An Oracle Machine Learning cloud service account **username** and **password** must be provided for authentication.\n\n### **REST API Workflow**\n\nIn this workflow, we highlight a few of the features of the REST API:\n\n- authenticating the database user and obtaining a token\n- loading a database table into the database\n- saving scripts in the database Python script repository\n- executing the saved Python scripts from the REST API using both synchronous and asynchronous modes\n\n\nCopyright (c) 2022 Oracle Corporation \n###### The Universal Permissive License (UPL), Version 1.0\n---", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:42:00+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "keys": [], - "values": [], - "groups": [], - "scatter": {} - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

OML4Py REST API for invoking embedded R execution

\n

On Oracle Autonomous Database, OML4Py contains a REST API to run user-defined Python functions saved in the script repository. REST APIs can be called from a web development application, improving the portability of the interface to other types of platforms, increasing project scalability, and allowing components to evolve independently. Use the OML4Py REST API to invoke user-defined Python functions and to list those available in the Python script repository

\n

To run a script, it must reside in the Python script repository. An Oracle Machine Learning cloud service account username and password must be provided for authentication.

\n

REST API Workflow

\n

In this workflow, we highlight a few of the features of the REST API:

\n
    \n
  • authenticating the database user and obtaining a token
    • \n
  • loading a database table into the database
    • \n
  • saving scripts in the database Python script repository
    • \n
  • executing the saved Python scripts from the REST API using both synchronous and asynchronous modes
    • \n
\n

Copyright (c) 2022 Oracle Corporation

\n
The Universal Permissive License (UPL), Version 1.0
\n
\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_1541796990", - "id": "20220701-211935_75320687", - "dateCreated": "2020-06-10T19:04:55+0000", - "dateStarted": "2022-08-01T15:39:19+0000", - "dateFinished": "2022-08-01T15:39:20+0000", - "status": "FINISHED", - "focus": true, - "$$hashKey": "object:41" - }, - { - "text": "%md\n\nOracle ADW Documentation https://docs.oracle.com/en/cloud/paas/autonomous-data-warehouse-cloud/index.html\nOML folder on Oracle Github : https://github.com/oracle/oracle-db-examples/tree/master/machine-learning\nOML web page: https://www.oracle.com/machine-learning", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Oracle ADW Documentation https://docs.oracle.com/en/cloud/paas/autonomous-data-warehouse-cloud/index.html\n
OML folder on Oracle Github : https://github.com/oracle/oracle-db-examples/tree/master/machine-learning\n
OML web page: https://www.oracle.com/machine-learning

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657060141674_422213772", - "id": "paragraph_1657060141674_422213772", - "dateCreated": "2022-07-05T22:29:01+0000", - "dateStarted": "2022-08-01T15:39:20+0000", - "dateFinished": "2022-08-01T15:39:20+0000", - "status": "FINISHED", - "$$hashKey": "object:42" - }, - { - "text": "%md\n\n### **REST API Authentication**\n\nTo authenticate and obtain a token, use **cURL** with the **-d** option to pass the credentials for your Oracle Machine Learning account against the Oracle Machine Learning user management cloud service REST endpoint */oauth2/v1/token*. \n\n $ curl -X POST --header 'Content-Type: application/json' --header 'Accept: application/json' -d '{\"grant_type\":\"password\", \"username\":\"''\", \n \"password\":\"' '\"}' \"/omlusers/api/oauth2/v1/token\"\n \nwhere \n\n* _-X POST_ specifies to use a POST request when communicating with the HTTP server\n* _--header_ defines the headers required for the request (application/json)\n* _-d _ sends the username and password authentication credentials as data in a POST request to the HTTP server\n* _Content-Type_ and _Accept_ define the response format (JSON)\n* _yourusername_ is the user name of a Oracle Machine Learning user with the default OML_DEVELOPER role\n* _yourpassword_ is the password for the user name\n* _oml-cloud-service-url_ is the REST server portion of the Oracle Machine Learning user management cloud service instance\n\nFor example, Oracle Machine Learning user **OMLUSER** with password **OMLPASSWD** and cloud service url **https://qtraya2braestch-omldb.adb.us-sanjose-1.oraclecloudapps.com** authenticates and obtain a REST token using the following approach:\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": { - "oml_server": "" - }, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

REST API Authentication

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To authenticate and obtain a token, use cURL with the -d option to pass the credentials for your Oracle Machine Learning account against the Oracle Machine Learning user management cloud service REST endpoint /oauth2/v1/token.

\n
$ curl -X POST --header 'Content-Type: application/json' --header 'Accept: application/json' -d '{\"grant_type\":\"password\", \"username\":\"'<yourusername>'\", \n\"password\":\"' <yourpassword>'\"}' \"<oml-cloud-service-url>/omlusers/api/oauth2/v1/token\"\n
\n

where

\n
    \n
  • -X POST specifies to use a POST request when communicating with the HTTP server
    • \n
  • –header defines the headers required for the request (application/json)
    • \n
  • -d sends the username and password authentication credentials as data in a POST request to the HTTP server
    • \n
  • Content-Type and Accept define the response format (JSON)
    • \n
  • yourusername is the user name of a Oracle Machine Learning user with the default OML_DEVELOPER role
    • \n
  • yourpassword is the password for the user name
    • \n
  • oml-cloud-service-url is the REST server portion of the Oracle Machine Learning user management cloud service instance
    • \n
\n

For example, Oracle Machine Learning user OMLUSER with password OMLPASSWD and cloud service url https://qtraya2braestch-omldb.adb.us-sanjose-1.oraclecloudapps.com authenticates and obtain a REST token using the following approach:

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-1694404374", - "id": "20220701-211935_1822215302", - "dateCreated": "2020-06-14T18:38:33+0000", - "dateStarted": "2022-08-01T15:39:21+0000", - "dateFinished": "2022-08-01T15:39:21+0000", - "status": "FINISHED", - "$$hashKey": "object:43" - }, - { - "text": "%md\n___________________________________________________________________________________________________________________________________________________________________________________________________________________________\nExport the OML cloud service URL to the environment variable `omlserver`, the OML username to environment variable `username`, and the password to environment variable `password`, then exchange the OML user credentials for an access token using a `cURL` command.\n\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "
\n

Export the OML cloud service URL to the environment variable omlserver, the OML username to environment variable username, and the password to environment variable password, then exchange the OML user credentials for an access token using a cURL command.

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-1728963585", - "id": "20220701-211935_1235404262", - "dateCreated": "2020-08-11T23:07:01+0000", - "dateStarted": "2022-08-01T15:39:21+0000", - "dateFinished": "2022-08-01T15:39:21+0000", - "status": "FINISHED", - "$$hashKey": "object:44" - }, - { - "text": "\n$ export omlserver=https://qtraya2braestch-omldb.adb.us-sanjose-1.oraclecloudapps.com\n$ export username=OMLUSER\n$ export password=OMLPASSWD\n\ncurl -i -X POST --header 'Content-Type: application/json' --header 'Accept: application/json' -d '{\"grant_type\":\"password\", \"username\":\"'${username}'\", \"password\":\"'${password}'\"}' \"${omlserver}/omlusers/api/oauth2/v1/token\"\n\n HTTP/1.1 200 OK\n Date: Wed, 09 Mar 2022 21:59:16 GMT\n Content-Type: application/json\n Content-Length: 1027\n Connection: keep-alive\n Cache-Control: no-cache, no-store, private\n X-Frame-Options: SAMEORIGIN\n X-XSS-Protection: 1;mode=block\n Strict-Transport-Security: max-age=31536000; includeSubDomains\n X-Content-Type-Options: nosniff\n\n {\"accessToken\":\"eyJhbGciOiJ...\",\"expiresIn\":3600,\"tokenType\":\"Bearer\"}\n\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "results": {}, - "enabled": false - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-1772971452", - "id": "20220701-211935_662630565", - "dateCreated": "2020-08-11T23:04:41+0000", - "status": "FINISHED", - "$$hashKey": "object:45" - }, - { - "text": "%md \n______________________________________________________________________________________________________________________________________________________________________________________________________________________________\nCopy the `accessToken` field from the response and assign it to variable token, surrounded by single quotes. A token has a lifecycle of 3600 seconds, or 1 hour, and it can be refreshed for up to 8 hours.", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "
\n

Copy the accessToken field from the response and assign it to variable token, surrounded by single quotes. A token has a lifecycle of 3600 seconds, or 1 hour, and it can be refreshed for up to 8 hours.

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-908807997", - "id": "20220701-211935_1233573648", - "dateCreated": "2020-08-11T23:07:51+0000", - "dateStarted": "2022-08-01T15:39:22+0000", - "dateFinished": "2022-08-01T15:39:22+0000", - "status": "FINISHED", - "$$hashKey": "object:46" - }, - { - "text": "$ export token='eyJhbGciOiJ...'", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": false, - "results": {}, - "enabled": false - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_854245908", - "id": "20220701-211935_1131727450", - "dateCreated": "2020-08-11T23:08:13+0000", - "status": "FINISHED", - "$$hashKey": "object:47" - }, - { - "title": "Load a Python DataFrame to an Oracle Database table", - "text": "%md\n______________________________________________________________________________________________________________________________________________________________________________________________________________________________\nUsing the `oml.create` function, create an OML proxy object `IRIS_PY` from the `iris` data. The OML proxy object `IRIS_PY` represents a database table. We first drop the table if already exists, and display the first 6 rows of the `IRIS_PY` proxy object. \n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "
\n

Using the oml.create function, create an OML proxy object IRIS_PY from the iris data. The OML proxy object IRIS_PY represents a database table. We first drop the table if already exists, and display the first 6 rows of the IRIS_PY proxy object.

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-612926384", - "id": "20220701-211935_472295975", - "dateCreated": "2020-06-14T19:55:10+0000", - "dateStarted": "2022-08-01T15:39:22+0000", - "dateFinished": "2022-08-01T15:39:22+0000", - "status": "FINISHED", - "$$hashKey": "object:48" - }, - { - "text": "%python\n\nimport oml\nimport pandas as pd\nfrom sklearn.datasets import load_iris\n\niris = load_iris()\nX = pd.DataFrame(iris.data, \n columns = [\"SEPAL_LENGTH\", \"SEPAL_WIDTH\", \"PETAL_LENGTH\", \"PETAL_WIDTH\"])\ny = pd.DataFrame(list(map(lambda x: {0:'setosa', 1: 'versicolor', 2:'virginica'}[x], iris.target)), \n columns = ['SPECIES'])\n\niris_df = pd.concat([X, y], axis=1)\ntry:\n oml.drop(table='IRIS_PY')\nexcept:\n pass\nIRIS_PY = oml.create(iris_df, table = 'IRIS_PY')\n\nz.show(IRIS_PY.head())\n\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "editorHide": false, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "SEPAL_LENGTH": "string", - "SEPAL_WIDTH": "string", - "PETAL_LENGTH": "string", - "PETAL_WIDTH": "string", - "SPECIES": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "SEPAL_LENGTH\tSEPAL_WIDTH\tPETAL_LENGTH\tPETAL_WIDTH\tSPECIES\n4.6\t3.6\t1\t0.2\tsetosa\n5.1\t2.5\t3\t1.1\tversicolor\n6.0\t2.2\t4\t1.0\tversicolor\n5.8\t2.6\t4\t1.2\tversicolor\n5.5\t2.3\t4\t1.3\tversicolor\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-622627243", - "id": "20220701-211935_1275955934", - "dateCreated": "2020-06-14T19:56:19+0000", - "dateStarted": "2022-08-01T15:39:23+0000", - "dateFinished": "2022-08-01T15:39:34+0000", - "status": "FINISHED", - "$$hashKey": "object:49" - }, - { - "title": "Create a Python script and save it to the Python script repository", - "text": "%md\n\n____________________________________________________________________________________________________________________________________________________________________________________________________________________________\nCreate a function `group_count_py` that returns the counts for each category in the `SPECIES` column. Save the `group_count_py` function to the Python script repository using `oml.script.create`, overwriting any existing script with the same name. The script is invoked from the Python interface, followed by the OML4Py Python and REST APIs for embedded Python execution.\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "
\n

Create a function group_count_py that returns the counts for each category in the SPECIES column. Save the group_count_py function to the Python script repository using oml.script.create, overwriting any existing script with the same name. The script is invoked from the Python interface, followed by the OML4Py Python and REST APIs for embedded Python execution.

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_47057711", - "id": "20220701-211935_869071384", - "dateCreated": "2020-06-14T18:31:13+0000", - "dateStarted": "2022-08-01T15:39:34+0000", - "dateFinished": "2022-08-01T15:39:34+0000", - "status": "FINISHED", - "$$hashKey": "object:50" - }, - { - "text": "%python\n\ndef group_count_py(dat):\n import pandas as pd\n return pd.DataFrame([(dat[\"SPECIES\"][0], dat.shape[0])], columns = [\"SPECIES\", \"COUNT\"])\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656712042931_2103424631", - "id": "paragraph_1656712042931_2103424631", - "dateCreated": "2022-07-01T21:47:22+0000", - "dateStarted": "2022-08-01T15:39:34+0000", - "dateFinished": "2022-08-01T15:39:34+0000", - "status": "FINISHED", - "$$hashKey": "object:51" - }, - { - "title": "Run the script in Python", - "text": "%python\n\ngroup_count_py(iris_df)", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TEXT", - "data": " SPECIES COUNT\n0 setosa 150\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656711237727_641436192", - "id": "paragraph_1656711237727_641436192", - "dateCreated": "2022-07-01T21:33:57+0000", - "dateStarted": "2022-08-01T15:39:34+0000", - "dateFinished": "2022-08-01T15:39:34+0000", - "status": "FINISHED", - "$$hashKey": "object:52" - }, - { - "text": "%python\n\ngroup_count_py = \"\"\"def group_count_py(dat):\n import oml\n import pandas as pd\n return pd.DataFrame([(dat[\"SPECIES\"][0], dat.shape[0])], columns = [\"SPECIES\", \"COUNT\"])\"\"\"\n\n\noml.script.create(\"group_count_py\", func=group_count_py, overwrite=True) \n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "editorHide": false, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-233208377", - "id": "20220701-211935_1452261409", - "dateCreated": "2020-06-14T20:17:35+0000", - "dateStarted": "2022-08-01T15:39:35+0000", - "dateFinished": "2022-08-01T15:39:35+0000", - "status": "FINISHED", - "$$hashKey": "object:53" - }, - { - "title": "View the Python script in the script repository", - "text": "%md\n\nTo check for the existence of the saved `group_count_py` script from the OML4Py Python interface, run the function `oml.script.dir`.", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

To check for the existence of the saved group_count_py script from the OML4Py Python interface, run the function oml.script.dir.

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_1166399989", - "id": "20220701-211935_1596588315", - "dateCreated": "2020-06-15T21:48:12+0000", - "dateStarted": "2022-08-01T15:39:35+0000", - "dateFinished": "2022-08-01T15:39:35+0000", - "status": "FINISHED", - "$$hashKey": "object:54" - }, - { - "text": "%python\n\noml.script.dir(sctype='all')[['name', 'owner']]\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "editorHide": false, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TEXT", - "data": " name owner\n0 build_lm_py OMLUSER\n1 group_count_py OMLUSER\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-1502485307", - "id": "20220701-211935_190987484", - "dateCreated": "2020-06-15T21:50:56+0000", - "dateStarted": "2022-08-01T15:39:35+0000", - "dateFinished": "2022-08-01T15:39:35+0000", - "status": "FINISHED", - "$$hashKey": "object:55" - }, - { - "title": "Run the script using group_apply", - "text": "%md\n\nThe `group_apply` function runs a user-defined function on data grouped by a specified column in the database environment. In this case, the grouping column is `SPECIES` and the script is `group_count_py`.\n\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

The group_apply function runs a user-defined function on data grouped by a specified column in the database environment. In this case, the grouping column is SPECIES and the script is group_count_py.

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657060920645_1371888580", - "id": "paragraph_1657060920645_1371888580", - "dateCreated": "2022-07-05T22:42:00+0000", - "dateStarted": "2022-08-01T15:39:36+0000", - "dateFinished": "2022-08-01T15:39:36+0000", - "status": "FINISHED", - "$$hashKey": "object:56" - }, - { - "text": "%python\n\nindex = IRIS_PY['SPECIES']\n\nres = oml.group_apply(IRIS_PY, index, func=group_count_py, oml_input_type=\"pandas.DataFrame\")\n\nres", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "SPECIES": "string", - "SEPAL_LENGTH": "string", - "COUNT": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TEXT", - "data": "{'virginica': SPECIES COUNT\n0 virginica 50, 'setosa': SPECIES COUNT\n0 setosa 50, 'versicolor': SPECIES COUNT\n0 versicolor 50}\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_1475070891", - "id": "20220701-211935_2144415557", - "dateCreated": "2020-06-14T21:10:59+0000", - "dateStarted": "2022-08-01T15:39:36+0000", - "dateFinished": "2022-08-01T15:39:37+0000", - "status": "FINISHED", - "$$hashKey": "object:57" - }, - { - "text": "%md\n\n### **Synchronous REST API calls**", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": { - "oml_server": "", - "token": "" - }, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Synchronous REST API calls

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_1263326668", - "id": "20220701-211935_600075097", - "dateCreated": "2020-06-10T19:08:58+0000", - "dateStarted": "2022-08-01T15:39:38+0000", - "dateFinished": "2022-08-01T15:39:38+0000", - "status": "FINISHED", - "$$hashKey": "object:58" - }, - { - "title": "View script in the Python script repository using REST", - "text": "%md\n\nVerify the existence of `group_count_py` in the script repository again, this time using the REST API with `cURL`. Send a GET request to the scripts endpoint, and the scripts available to the OML user are returned in JSON format.\n\nNote, the default REST API execution mode is synchronous, so code execution will wait for the REST API call to return before additional calls may be initiated.", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Verify the existence of group_count_py in the script repository again, this time using the REST API with cURL. Send a GET request to the scripts endpoint, and the scripts available to the OML user are returned in JSON format.

\n

Note, the default REST API execution mode is synchronous, so code execution will wait for the REST API call to return before additional calls may be initiated.

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656713836978_1113346416", - "id": "paragraph_1656713836978_1113346416", - "dateCreated": "2022-07-01T22:17:16+0000", - "dateStarted": "2022-08-01T15:39:38+0000", - "dateFinished": "2022-08-01T15:39:38+0000", - "status": "FINISHED", - "$$hashKey": "object:59" - }, - { - "text": "\r\n$ curl -X GET --header \"Authorization: Bearer ${token}\" --header 'Accept: application/json' \"${omlserver}/oml/api/py-scripts/v1/scripts\" | jq '.result[] | .name + \" \" + .owner'\r\n\r\n HTTP/1.1 200 OK\r\n Date: Wed, 09 Mar 2022 21:44:39 GMT\r\n Content-Type: application/json\r\n Transfer-Encoding: chunked\r\n Connection: keep-alive\r\n Cache-Control: no-cache, no-store, private\r\n X-Frame-Options: SAMEORIGIN\r\n X-XSS-Protection: 1;mode=block\r\n Strict-Transport-Security: max-age=31536000; includeSubDomains\r\n X-Content-Type-Options: nosniff\r\n\r\n \"group_count OWNER\"", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "results": {}, - "enabled": false - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_1350713939", - "id": "20220701-211935_1436144483", - "dateCreated": "2020-08-11T23:42:57+0000", - "status": "FINISHED", - "$$hashKey": "object:60" - }, - { - "text": "%md\n\nInvoke the `group_count` function in the script repository from the REST API. Set `parallelFlag` to true to leverage database parallelism.\n\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Invoke the group_count function in the script repository from the REST API. Set parallelFlag to true to leverage database parallelism.

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_1303382259", - "id": "20220701-211935_1513366034", - "dateCreated": "2020-06-15T22:12:33+0000", - "dateStarted": "2022-08-01T15:39:38+0000", - "dateFinished": "2022-08-01T15:39:38+0000", - "status": "FINISHED", - "$$hashKey": "object:61" - }, - { - "text": "\n\n\n$ curl -i -X POST --header \"Authorization: Bearer ${token}\" --header 'Content-Type: application/json' --header 'Accept: application/json' -d '{\"input\":\"select * from IRIS\", \"parameters\":\"{\\\"oml_input_type\\\":\\\"pandas.DataFrame\\\"}\", \"groupBy\":\"SPECIES\", \"orderBy\":\"SEPAL_LENGTH\", \"parallelFlag\":true}' \"${omlserver}/oml/api/py-scripts/v1/group-apply/group_count\"\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "results": {}, - "enabled": false - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-76982211", - "id": "20220701-211935_1076519252", - "dateCreated": "2020-08-07T16:40:17+0000", - "status": "FINISHED", - "$$hashKey": "object:62" - }, - { - "text": "%md\n\n\nThe result of the REST execution is a JSON representation of the value returned from the Python script. Dataframes, lists, and dictionaries and PNG images are supported. The returned value is:\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

The result of the REST execution is a JSON representation of the value returned from the Python script. Dataframes, lists, and dictionaries and PNG images are supported. The returned value is:

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_315734315", - "id": "20220701-211935_1077171371", - "dateCreated": "2020-08-11T23:46:39+0000", - "dateStarted": "2022-08-01T15:39:39+0000", - "dateFinished": "2022-08-01T15:39:39+0000", - "status": "FINISHED", - "$$hashKey": "object:63" - }, - { - "text": "\n\n\n{\"result\":{\"versicolor_8\":{\"SEPAL_LENGTH\":{\"0\":5.7},\"SPECIES\":{\"0\":\"versicolor\"},\"CNT\":{\"0\":5}},\"versicolor_7\":{\"SEPAL_LENGTH\":{\"0\":5.6},\"SPECIES\":{\"0\":\"versicolor\"},\"CNT\":{\"0\":2}},\"virginica_20\":{\"SEPAL_LENGTH\":{\"0\":6.7},\"SPECIES\":{\"0\":\"virginica\"},.....\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "results": {}, - "enabled": false - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_576585122", - "id": "20220701-211935_1538098437", - "dateCreated": "2020-08-11T23:46:57+0000", - "status": "FINISHED", - "$$hashKey": "object:64" - }, - { - "text": "%md\n\n### **Asynchronous REST API calls**\n\nAsynchronous calls do not wait for the result to return from the server. If the Python script is performing long running computations, results will not be immediate and the user may want to use asynchronous calls to continue development on the client.\n\nThe asynchronous call's returned results are included in the response header. Display the response header by passing the `-i` flag to the `cURL` command. Asynchronous calls have a default timeout of 1800 seconds, or 30 minutes, and can be extended up to 12 hours. Set the `asyncFlag` to `true` to run asynchronous calls from the REST API.\n\n\n\n ", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": { - "token": "", - "oml_server": "" - }, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Asynchronous REST API calls

\n

Asynchronous calls do not wait for the result to return from the server. If the Python script is performing long running computations, results will not be immediate and the user may want to use asynchronous calls to continue development on the client.

\n

The asynchronous call's returned results are included in the response header. Display the response header by passing the -i flag to the cURL command. Asynchronous calls have a default timeout of 1800 seconds, or 30 minutes, and can be extended up to 12 hours. Set the asyncFlag to true to run asynchronous calls from the REST API.

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-879204689", - "id": "20220701-211935_552736976", - "dateCreated": "2020-06-10T19:10:49+0000", - "dateStarted": "2022-08-01T15:39:40+0000", - "dateFinished": "2022-08-01T15:39:40+0000", - "status": "FINISHED", - "$$hashKey": "object:65" - }, - { - "text": "\n\n$ curl -i -X POST --header \"Authorization: Bearer ${token}\" --header 'Content-Type: application/json' --header 'Accept: application/json' -d '{\"asyncFlag\":true, \"input\":\"select * from IRIS\", \"parameter\":\"{\\\"oml_input_type\\\":\\“pandas.DataFrame\\\"}\", \"groupBy\":\"SPECIES\", \"parallelFlag\":true}' \"${omlserver}/oml/api/py-scripts/v1/group-apply/group_count_py\"\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "results": {}, - "enabled": false - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-1732335601", - "id": "20220701-211935_868351323", - "dateCreated": "2020-08-11T23:48:30+0000", - "status": "FINISHED", - "$$hashKey": "object:66" - }, - { - "title": "Perform an asynchronous REST call with a timeout of 300 seconds, or 5 minutes", - "text": "%md\r\n\r\nBelow is the equivalent asynchronous REST call with a timeout of 300 seconds, or 5 minutes. The output includes the HTTP 201 status code indicating the job was created, and a job id location that can be polled for status and results.\r\n\r\nThe `timeout` flag is used to change the default timeout setting.", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Below is the equivalent asynchronous REST call with a timeout of 300 seconds, or 5 minutes. The output includes the HTTP 201 status code indicating the job was created, and a job id location that can be polled for status and results.

\n

The timeout flag is used to change the default timeout setting.

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_1821911865", - "id": "20220701-211935_1362257540", - "dateCreated": "2020-08-11T23:49:32+0000", - "dateStarted": "2022-08-01T15:39:40+0000", - "dateFinished": "2022-08-01T15:39:40+0000", - "status": "FINISHED", - "$$hashKey": "object:67" - }, - { - "text": "\n\n$ curl -i -X POST --header \"Authorization: Bearer ${token}\" --header 'Content-Type: application/json' --header 'Accept: application/json' -d '{\"asyncFlag\":true,\"timeout\":300, \"input\":\"select * from IRIS\", \"parameter\":\"{\\\"oml_input_type\\\":\\\"pandas.DataFrame\\\"}\", \"groupBy\":\"SPECIES\", \"parallelFlag\":true}' \"${omlserver}/oml/api/py-scripts/v1/group-apply/group_count_py\"\n\n HTTP/1.1 201 Created\n Location: $ {oml_server}/oml/tenants/MYTENANT/databases/MYADW/api/py-scripts/v1/\n Cache-Control: no-cache, no-store, private\n Content-Length: 0\n X-Frame-Options: SAMEORIGIN\n Proxy-Connection: Keep-Alive\n X-XSS-Protection: 1;mode=block\n X-Content-Type-Options: nosniff\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "results": {}, - "enabled": false - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-1049760695", - "id": "20220701-211935_1719682058", - "dateCreated": "2020-08-11T23:49:59+0000", - "status": "FINISHED", - "$$hashKey": "object:68" - }, - { - "title": "Poll the job status", - "text": "%md\n\nTo poll the job status, pass the job ID location to the jobs endpoint using the GET method. The HTTP response status 302 indicates the running job is found and includes a job id location for future results.\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

To poll the job status, pass the job ID location to the jobs endpoint using the GET method. The HTTP response status 302 indicates the running job is found and includes a job id location for future results.

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-1079793725", - "id": "20220701-211935_1443161234", - "dateCreated": "2020-06-15T22:41:51+0000", - "dateStarted": "2022-08-01T15:39:41+0000", - "dateFinished": "2022-08-01T15:39:41+0000", - "status": "FINISHED", - "$$hashKey": "object:69" - }, - { - "text": "\n$ curl -i -X GET --header \"Authorization: Bearer ${token}\" --header 'Accept: application/json' ${omlserver}/oml/api/py-scripts/v1/jobs/\n\n HTTP/1.1 302 Found\n Date: Wed, 09 Mar 2022 13:04:04 GMT\n Server: nginx/1.18.0\n Cache-Control: no-cache, no-store, private\n Content-Length: 0\n X-Frame-Options: SAMEORIGIN\n Content-Location: http:///oml/tenants/TENANT1/databases/ADWP/api/py-scripts/v1//result\n Proxy-Connection: Keep-Alive\n X-XSS-Protection: 1;mode=block\n X-Content-Type-Options: nosniff", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "results": {}, - "enabled": false - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_720143535", - "id": "20220701-211935_1779691564", - "dateCreated": "2020-08-11T23:55:20+0000", - "status": "FINISHED", - "$$hashKey": "object:70" - }, - { - "title": "Poll the job at the results location", - "text": "\r\n$ curl -i -X GET --header \"Authorization: Bearer ${token}\" --header 'Accept: application/json' ${omlserver}/oml/api/py-scripts/v1/jobs//result\r\n\r\n\r\n HTTP/1.1 200 OK\r\n Date: Wed, 09 Mar 2022 13:06:05 GMT\r\n Server: nginx/1.18.0\r\n Content-Type: application/json\r\n Cache-Control: no-cache, no-store, private\r\n Content-Length: 1038\r\n X-Frame-Options: SAMEORIGIN\r\n Proxy-Connection: Keep-Alive\r\n X-XSS-Protection: 1;mode=block\r\n X-Content-Type-Options: nosniff", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": false - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_1111047527", - "id": "20220701-211935_1276320936", - "dateCreated": "2020-08-11T23:57:32+0000", - "status": "FINISHED", - "$$hashKey": "object:71" - }, - { - "text": "%md\n\nThe returned value is:\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

The returned value is:

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_175250465", - "id": "20220701-211935_1036141004", - "dateCreated": "2020-08-11T23:58:58+0000", - "dateStarted": "2022-08-01T15:39:41+0000", - "dateFinished": "2022-08-01T15:39:41+0000", - "status": "FINISHED", - "$$hashKey": "object:72" - }, - { - "text": "\n\n\n{\"result\":{\"versicolor_8\":{\"SEPAL_LENGTH\":{\"0\":5.7},\"SPECIES\":{\"0\":\"versicolor\"},\"CNT\":{\"0\":5}},\"versicolor_7\":{\"SEPAL_LENGTH\":{\"0\":5.6},\"SPECIES\":{\"0\":\"versicolor\"},\"CNT\":{\"0\":2}},\"virginica_20\":{\"SEPAL_LENGTH\":{\"0\":6.7},\"SPECIES\":{\"0\":\"virginica\"},.....\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "results": {}, - "enabled": false - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-1731593710", - "id": "20220701-211935_1210406088", - "dateCreated": "2020-08-11T23:59:11+0000", - "status": "FINISHED", - "$$hashKey": "object:73" - }, - { - "title": "Returning model details from the REST API", - "text": "%md\n\n\nLet's create a linear model script and run it from the REST API. First, we'll define our function, `build_lm_py`, which returns a dict mapping of the model attributes. Note that the model itself cannot be returned directly from REST because LinearRegression model objects are not JSON-serializable. \n\n\n\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Let's create a linear model script and run it from the REST API. First, we'll define our function, build_lm_py, which returns a dict mapping of the model attributes. Note that the model itself cannot be returned directly from REST because LinearRegression model objects are not JSON-serializable.

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_1954297624", - "id": "20220701-211935_1560951469", - "dateCreated": "2020-08-18T21:01:09+0000", - "dateStarted": "2022-08-01T15:39:42+0000", - "dateFinished": "2022-08-01T15:39:42+0000", - "status": "FINISHED", - "$$hashKey": "object:74" - }, - { - "text": "%python\n\nbuild_lm_py = \"\"\"def build_py(dat):\n from sklearn import linear_model\n import oml\n regr = linear_model.LinearRegression()\n import pandas as pd\n dat = pd.get_dummies(dat, drop_first=True)\n X = dat[[\"SEPAL_WIDTH\", \"PETAL_LENGTH\", \"PETAL_WIDTH\", \"SPECIES_versicolor\", \"SPECIES_virginica\"]]\n y = dat[[\"SEPAL_LENGTH\"]]\n regr.fit(X, y)\n data = {}\n data[\"init_params\"] = regr.get_params()\n data[\"model_params\"] = mp = {}\n for p in (\"coef_\", \"intercept_\", \"_residues\", \"singular_\"):\n mp[p] = getattr(regr, p).tolist()\n return data\"\"\"\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_425530666", - "id": "20220701-211935_153656312", - "dateCreated": "2020-08-18T21:26:57+0000", - "dateStarted": "2022-08-01T15:39:42+0000", - "dateFinished": "2022-08-01T15:39:42+0000", - "status": "FINISHED", - "$$hashKey": "object:75" - }, - { - "title": "Save the script to the Python script repository", - "text": "%python\n\noml.script.create(\"build_lm_py\", func=build_lm_py, overwrite=True) \n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "text", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/undefined", - "fontSize": 9, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_441791799", - "id": "20220701-211935_1143665701", - "dateCreated": "2020-08-18T20:16:08+0000", - "dateStarted": "2022-08-01T15:39:43+0000", - "dateFinished": "2022-08-01T15:39:43+0000", - "status": "FINISHED", - "$$hashKey": "object:76" - }, - { - "text": "%md\n_________________________________________________________________________________________________________________________________________________________________________________________________________________________\nNow invoke the build_lm_rest_py function from the REST API in asynchronous mode.\n\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "
\n

Now invoke the build_lm_rest_py function from the REST API in asynchronous mode.

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-1945409867", - "id": "20220701-211935_1224302943", - "dateCreated": "2020-08-18T21:35:47+0000", - "dateStarted": "2022-08-01T15:39:43+0000", - "dateFinished": "2022-08-01T15:39:43+0000", - "status": "FINISHED", - "$$hashKey": "object:77" - }, - { - "text": "\n\n$ curl -i -X POST --header \"Authorization: Bearer ${token}\" --header 'Content-Type: application/json' --header 'Accept: application/json' -d '{\"input\":\"select * from IRIS\", \"parameters\":\"{\\\"oml_input_type\\\":\\\"pandas.DataFrame\\\"}\"}' \"${omlserver}/oml/api/py-scripts/v1/table-apply/build_lm_py\"\n", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "results": {}, - "enabled": false - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-529279554", - "id": "20220701-211935_96720099", - "dateCreated": "2020-08-20T20:39:17+0000", - "status": "FINISHED", - "$$hashKey": "object:78" - }, - { - "text": "%md\n\nThe returned value is a dict containing model attributes.", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

The returned value is a dict containing model attributes.

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_-1252944791", - "id": "20220701-211935_2026652044", - "dateCreated": "2020-08-18T21:38:20+0000", - "dateStarted": "2022-08-01T15:39:43+0000", - "dateFinished": "2022-08-01T15:39:43+0000", - "status": "FINISHED", - "$$hashKey": "object:79" - }, - { - "text": "\n{\"result\":{\"init_params\":{\"fit_intercept\":true,\"n_jobs\":null,\"normalize\":false,\"copy_X\":true},\"model_params\":{\"intercept_\":[2.1712662921550736],\"_residues\":[13.556485081974792],\"coef_\":[[0.4958889383885511,0.8292439122348054,-0.315155173326473,-0.7235619577807288,-1.0234978144908309]],\"singular_\":[23.873627650888057,7.279716799977891,4.192696791126727,2.194192042042924,0.7289542732694926]}}}", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "results": {}, - "enabled": false - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_243743032", - "id": "20220701-211935_1747218128", - "dateCreated": "2020-08-18T20:56:59+0000", - "status": "FINISHED", - "$$hashKey": "object:80" - }, - { - "text": "%md\n# End of Script", - "user": "OMLUSER", - "dateUpdated": "2022-08-01T15:39:44+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

End of Script

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1656710375533_1881413655", - "id": "20220701-211935_1935399931", - "dateCreated": "2020-06-10T19:13:37+0000", - "dateStarted": "2022-08-01T15:39:44+0000", - "dateFinished": "2022-08-01T15:39:44+0000", - "status": "FINISHED", - "$$hashKey": "object:81" - } - ], - "name": "OML4Py REST API", - "id": "19315", - "defaultInterpreterGroup": "spark", - "noteParams": {}, - "noteForms": { - "oml_server": { - "type": "FormInput", - "name": "oml_server", - "defaultValue": "", - "hidden": false - } - }, - "angularObjects": {}, - "config": { - "looknfeel": "default", - "personalizedMode": "false" - }, - "info": { - "isRunning": false - }, - "path": "/OML4Py REST API" -} \ No newline at end of file diff --git a/machine-learning/notebooks/r/OML4SQL Feature Extraction ESA Wiki Model.json b/machine-learning/notebooks/r/OML4SQL Feature Extraction ESA Wiki Model.json deleted file mode 100644 index 8f3beb75..00000000 --- a/machine-learning/notebooks/r/OML4SQL Feature Extraction ESA Wiki Model.json +++ /dev/null @@ -1,1377 +0,0 @@ -{ - "paragraphs": [ - { - "text": "%md\n\n## Explicit Semantic Analysis (ESA) for Text Analytics\n\nExplicit Semantic Analysis (ESA) is an unsupervised algorithm for feature extraction of explicit features based on an existing knowledge base. It is the process of understanding the meaning of a section of text as a combination of the concepts found in the text. Compared to other techniques such as Latent Dirichlet Association (LDA) or Term Frequency-Inverse Document Frequency (TF-IDF), ESA offers some unique benefits. Most notably, it improves text document categorization by calculating *semantic relatedness* (how similar in meaning two words or pieces of text are to each other) between the documents and a set of topics that are explicitly defined and described by humans.\n\nOracle Machine Learning for SQL ESA extracts text-based features from a corpus of documents and performs document similarity comparisons. In this notebook, we'll use the Wikipedia Model as an example:\n\n- Create an ESA model object for the pre-loaded Wikipedia model \n- Examples of using the Wiki ESA model\n- Basic ESA Wiki model features for words\n- Basic ESA Wiki model features for phrases\n- ESA Wiki Model document similarity on phrases\n- ESA Wiki Model document similarity on long phrases\n\n*Note: The pre-built Wikipedia model must be installed in your Autonomous Database instance to run this notebook. See instructions below.*\n\nCopyright (c) 2022 Oracle Corporation \n###### The Universal Permissive License (UPL), Version 1.0\n---", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:02+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "keys": [], - "values": [], - "groups": [], - "scatter": {} - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Explicit Semantic Analysis (ESA) for Text Analytics

\n

Explicit Semantic Analysis (ESA) is an unsupervised algorithm for feature extraction of explicit features based on an existing knowledge base. It is the process of understanding the meaning of a section of text as a combination of the concepts found in the text. Compared to other techniques such as Latent Dirichlet Association (LDA) or Term Frequency-Inverse Document Frequency (TF-IDF), ESA offers some unique benefits. Most notably, it improves text document categorization by calculating semantic relatedness (how similar in meaning two words or pieces of text are to each other) between the documents and a set of topics that are explicitly defined and described by humans.

\n

Oracle Machine Learning for SQL ESA extracts text-based features from a corpus of documents and performs document similarity comparisons. In this notebook, we'll use the Wikipedia Model as an example:

\n
    \n
  • Create an ESA model object for the pre-loaded Wikipedia model
    • \n
  • Examples of using the Wiki ESA model
    • \n
  • Basic ESA Wiki model features for words
    • \n
  • Basic ESA Wiki model features for phrases
    • \n
  • ESA Wiki Model document similarity on phrases
    • \n
  • ESA Wiki Model document similarity on long phrases
    • \n
\n

Note: The pre-built Wikipedia model must be installed in your Autonomous Database instance to run this notebook. See instructions below.

\n

Copyright (c) 2022 Oracle Corporation

\n
The Universal Permissive License (UPL), Version 1.0
\n
\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_1962901923", - "id": "20220711-195144_1876911279", - "dateCreated": "2021-07-26T17:54:53+0000", - "dateStarted": "2022-07-29T19:21:02+0000", - "dateFinished": "2022-07-29T19:21:02+0000", - "status": "FINISHED", - "focus": true, - "$$hashKey": "object:41" - }, - { - "title": "For more information...", - "text": "%md\n\nOracle ADW Documentation https://docs.oracle.com/en/cloud/paas/autonomous-data-warehouse-cloud/index.html\nOML folder on Oracle Github : https://github.com/oracle/oracle-db-examples/tree/master/machine-learning\nOML web page: https://www.oracle.com/machine-learning\nOML Explicit Semantic Analysis: https://www.oracle.com/goto/ml-explicit-semantic-analysis", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:02+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Oracle ADW Documentation https://docs.oracle.com/en/cloud/paas/autonomous-data-warehouse-cloud/index.html\n
OML folder on Oracle Github : https://github.com/oracle/oracle-db-examples/tree/master/machine-learning\n
OML web page: https://www.oracle.com/machine-learning\n
OML Explicit Semantic Analysis: https://www.oracle.com/goto/ml-explicit-semantic-analysis

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_1510123163", - "id": "20220711-195144_1899655580", - "dateCreated": "2021-07-26T18:02:52+0000", - "dateStarted": "2022-07-29T19:21:03+0000", - "dateFinished": "2022-07-29T19:21:03+0000", - "status": "FINISHED", - "$$hashKey": "object:42" - }, - { - "text": "%md\n\n# Using the Wikipedia model as an example\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:03+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Using the Wikipedia model as an example

\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_1861342843", - "id": "20220711-195144_1673378363", - "dateCreated": "2021-07-26T17:55:37+0000", - "dateStarted": "2022-07-29T19:21:03+0000", - "dateFinished": "2022-07-29T19:21:03+0000", - "status": "FINISHED", - "$$hashKey": "object:43" - }, - { - "title": "Delete existing policies and create new policies for the Wiki Lexer", - "text": "%script\n\nBEGIN CTX_DDL.DROP_POLICY('WIKI_TXTPOL'); \n EXCEPTION WHEN OTHERS THEN NULL; \nEND;\n\nBEGIN CTX_DDL.DROP_PREFERENCE( 'WIKI_LEXER'); \n EXCEPTION WHEN OTHERS THEN NULL; \nEND;\n\nBEGIN CTX_DDL.CREATE_PREFERENCE('WIKI_LEXER', \n 'BASIC_LEXER'); \nEND;\n\nBEGIN CTX_DDL.SET_ATTRIBUTE('WIKI_LEXER', \n 'INDEX_STEMS', \n 'ENGLISH'); \nEND;\n\nBEGIN CTX_DDL.CREATE_POLICY(POLICY_NAME => 'WIKI_TXTPOL', \n LEXER => 'WIKI_LEXER'); \nEND;", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:03+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "plsql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/plsql", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": {}, - "enabled": false - }, - "settings": { - "params": {}, - "forms": {} - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_1852237015", - "id": "20220711-195144_280853696", - "dateCreated": "2021-07-26T18:06:50+0000", - "status": "FINISHED", - "$$hashKey": "object:44" - }, - { - "text": "%md\n\n### The pre-built Wikipedia model must be loaded to the Oracle Autonomous Database. It is a relatively large model object at 800 MB.\n#### Follow the setup in template notebook *OML Import ESA Wiki Model*\n\n#### Relevant Oracle blogs:\n1. New Wikipedia-Based Cognitive Model Available for Text Processing \n2. Text Analytics using a pre-built Wikipedia-based Topic Model \n3. Explicit Semantic Analysis (ESA) for Text Analytics ", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:03+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

The pre-built Wikipedia model must be loaded to the Oracle Autonomous Database. It is a relatively large model object at 800 MB.

\n

Follow the setup in template notebook OML Import ESA Wiki Model

\n

Relevant Oracle blogs:

\n
    \n
  1. New Wikipedia-Based Cognitive Model Available for Text Processing
    2. \n
  2. Text Analytics using a pre-built Wikipedia-based Topic Model
    3. \n
  3. Explicit Semantic Analysis (ESA) for Text Analytics
    4. \n
\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_-69001852", - "id": "20220711-195144_80971876", - "dateCreated": "2021-07-26T18:07:52+0000", - "dateStarted": "2022-07-29T19:21:04+0000", - "dateFinished": "2022-07-29T19:21:04+0000", - "status": "FINISHED", - "$$hashKey": "object:45" - }, - { - "title": "Check to see if the pre-loaded model is available", - "text": "%sql\n\n-- We should expect one row with the model WIKI_MODEL\nSELECT MODEL_NAME, MINING_FUNCTION, ALGORITHM, ALGORITHM_TYPE, CREATION_DATE FROM USER_MINING_MODELS WHERE MODEL_NAME='WIKI_MODEL'\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:04+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 105, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "MODEL_NAME": "string", - "MINING_FUNCTION": "string", - "ALGORITHM": "string", - "ALGORITHM_TYPE": "string", - "CREATION_DATE": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "MODEL_NAME\tMINING_FUNCTION\tALGORITHM\tALGORITHM_TYPE\tCREATION_DATE\nWIKI_MODEL\tFEATURE_EXTRACTION\tEXPLICIT_SEMANTIC_ANALYS\tNATIVE\t2022-07-29 16:32:50\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_-2131052979", - "id": "20220711-195144_642232307", - "dateCreated": "2021-07-26T18:10:21+0000", - "dateStarted": "2022-07-29T19:21:04+0000", - "dateFinished": "2022-07-29T19:21:04+0000", - "status": "FINISHED", - "$$hashKey": "object:46" - }, - { - "title": "Display model settings", - "text": "%sql\n\nSELECT SETTING_NAME, SETTING_VALUE, SETTING_TYPE AS TYPE\n FROM USER_MINING_MODEL_SETTINGS\n WHERE MODEL_NAME = 'WIKI_MODEL'\nORDER BY SETTING_NAME;", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:04+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "SETTING_NAME": "string", - "SETTING_VALUE": "string", - "TYPE": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "SETTING_NAME\tSETTING_VALUE\tTYPE\nALGO_NAME\tALGO_EXPLICIT_SEMANTIC_ANALYS\tINPUT\nESAS_MIN_ITEMS\t25\tINPUT\nESAS_TOPN_FEATURES\t1000\tINPUT\nESAS_VALUE_THRESHOLD\t.00000001\tDEFAULT\nODMS_DETAILS\tODMS_ENABLE\tDEFAULT\nODMS_MISSING_VALUE_TREATMENT\tODMS_MISSING_VALUE_AUTO\tDEFAULT\nODMS_SAMPLING\tODMS_SAMPLING_DISABLE\tDEFAULT\nODMS_TEXT_MAX_FEATURES\t200000\tINPUT\nODMS_TEXT_MIN_DOCUMENTS\t5\tINPUT\nODMS_TEXT_POLICY_NAME\twiki_txtpol\tINPUT\nPREP_AUTO\tON\tDEFAULT\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_600345844", - "id": "20220711-195144_681944418", - "dateCreated": "2021-07-26T19:00:55+0000", - "dateStarted": "2022-07-29T19:21:04+0000", - "dateFinished": "2022-07-29T19:21:04+0000", - "status": "FINISHED", - "$$hashKey": "object:47" - }, - { - "title": "Get a list of model views", - "text": "%sql\n\nSELECT VIEW_NAME, VIEW_TYPE FROM USER_MINING_MODEL_VIEWS\nWHERE MODEL_NAME='WIKI_MODEL'\nORDER BY VIEW_NAME;", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:04+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "VIEW_NAME": "string", - "VIEW_TYPE": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "VIEW_NAME\tVIEW_TYPE\nDM$VAWIKI_MODEL\tExplicit Semantic Analysis Matrix\nDM$VFWIKI_MODEL\tExplicit Semantic Analysis Features\nDM$VGWIKI_MODEL\tGlobal Name-Value Pairs\nDM$VNWIKI_MODEL\tNormalization and Missing Value Handling\nDM$VSWIKI_MODEL\tComputed Settings\nDM$VWWIKI_MODEL\tModel Build Alerts\nDM$VXWIKI_MODEL\tText Features\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_-669968573", - "id": "20220711-195144_1401264074", - "dateCreated": "2021-07-26T19:03:09+0000", - "dateStarted": "2022-07-29T19:21:05+0000", - "dateFinished": "2022-07-29T19:21:05+0000", - "status": "FINISHED", - "$$hashKey": "object:48" - }, - { - "text": "%md\n\n# Examples using the Wiki ESA model\n---\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:05+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Examples using the Wiki ESA model

\n
\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_-1627377121", - "id": "20220711-195144_1267578230", - "dateCreated": "2021-07-26T18:16:38+0000", - "dateStarted": "2022-07-29T19:21:05+0000", - "dateFinished": "2022-07-29T19:21:05+0000", - "status": "FINISHED", - "$$hashKey": "object:49" - }, - { - "title": "Basic example of ESA features for the word 'Bank' using the Wikipedia model", - "text": "%sql\n\nSELECT S.FEATURE_ID, S.VALUE FROM\n (SELECT FEATURE_SET(WIKI_MODEL, 10 USING *) FSET FROM \n (SELECT 'BANK' AS TEXT FROM DUAL)) T,\n TABLE(T.FSET) S ORDER BY S.VALUE DESC", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:05+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "FEATURE_ID": "string", - "VALUE": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "FEATURE_ID\tVALUE\nBanking in India\t0.12073074740513993\nBanking in Australia\t0.1186153932769802\nBank of America\t0.11307155411695473\nBank\t0.10994163646234326\nCentral bank\t0.10780307790446561\nNational Bank Act\t0.10647042777456947\nStandard Bank\t0.10502497981253221\nBankBoston\t0.10474436983267525\nOnline banking\t0.10250315951850819\nBank of England\t0.09610674490262502\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_1615494002", - "id": "20220711-195144_1353626563", - "dateCreated": "2021-07-26T18:17:19+0000", - "dateStarted": "2022-07-29T19:21:05+0000", - "dateFinished": "2022-07-29T19:21:05+0000", - "status": "FINISHED", - "$$hashKey": "object:50" - }, - { - "title": "ESA features for the words 'NFL games' using the Wikipedia model", - "text": "%sql\n\nSELECT S.FEATURE_ID, S.VALUE FROM\n (SELECT FEATURE_SET(WIKI_MODEL, 10 USING *) FSET FROM \n (SELECT 'NFL Games' AS TEXT FROM DUAL)) T,\n TABLE(T.FSET) S ORDER BY S.VALUE DESC", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:05+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "FEATURE_ID": "string", - "VALUE": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "FEATURE_ID\tVALUE\nNational Football League\t0.1448362549796241\nNFL International Series\t0.13968414188865144\nThursday Night Football\t0.11436240954509867\nHistory of the National Football League championship\t0.11272129823985683\nChicago College All-Star Game\t0.11121297109987173\nNFL Network\t0.11007694516545648\nNFL Films\t0.10627056953318934\nThe NFL Today\t0.10292445567064071\nNational Football League Christmas games\t0.10104092801135917\nPlayoff Bowl\t0.09258723455526119\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_1707240813", - "id": "20220711-195144_1436910081", - "dateCreated": "2021-07-26T18:18:54+0000", - "dateStarted": "2022-07-29T19:21:06+0000", - "dateFinished": "2022-07-29T19:21:06+0000", - "status": "FINISHED", - "$$hashKey": "object:51" - }, - { - "title": "ESA Features for text about Astronomy using the Wikipedia model", - "text": "%sql\n\nSELECT S.FEATURE_ID, S.VALUE FROM (\n SELECT FEATURE_SET(WIKI_MODEL, 10 USING *) FSET FROM\n (SELECT \n 'A group of European-led astronomers has made a photograph of what appears to be a planet orbiting another star. If so, it would be the first confirmed picture of a world beyond our solar system.' \n AS text FROM dual)) T, TABLE(T.FSET) S ORDER BY S.VALUE DESC", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:06+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "FEATURE_ID": "string", - "VALUE": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "FEATURE_ID\tVALUE\nSolar System\t0.1783977405440812\nPlanets beyond Neptune\t0.16384415493902063\nPlanet Nine\t0.1556042629299215\nPlanet\t0.14360577141174127\nExoplanet\t0.14146374523098973\nFormation and evolution of the Solar System\t0.1380857932488385\nTerrestrial planet\t0.12349262676588602\nAstronomer\t0.11968229035028131\nSolar analog\t0.11919958268012823\nPlanetary habitability\t0.11168273107745952\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_-759565373", - "id": "20220711-195144_711025848", - "dateCreated": "2021-07-26T18:14:47+0000", - "dateStarted": "2022-07-29T19:21:06+0000", - "dateFinished": "2022-07-29T19:21:06+0000", - "status": "FINISHED", - "$$hashKey": "object:52" - }, - { - "title": "ESA Features for a text about diet and health using the Wikipedia model", - "text": "%sql\n\nSELECT S.FEATURE_ID, S.VALUE FROM\n (SELECT FEATURE_SET(WIKI_MODEL, 10 USING *) FSET FROM\n (SELECT \n 'Nearly 70 percent of Americans say they are careful about what they eat, and even more say diet is essential to good health, according to a new nationwide health poll in which obesity ranked second among the biggest health concerns.' AS TEXT FROM DUAL)) T,\n TABLE(T.FSET) S ORDER BY S.VALUE DESC", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:06+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "FEATURE_ID": "string", - "VALUE": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "FEATURE_ID\tVALUE\nObesity\t0.2381281204952319\nChildhood obesity\t0.21566128131005566\nRobert Wood Johnson Foundation\t0.1790547081969936\nHealth\t0.1723830168425817\nHealthy diet\t0.16671289147333318\nDieting\t0.142162115212373\nPaleolithic diet\t0.1386597097885653\nHealth education\t0.12498303889516335\nHealth equity\t0.1149008443204024\nPlant-based diet\t0.11425470702731559\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_-373987672", - "id": "20220711-195144_207700615", - "dateCreated": "2021-07-26T18:20:16+0000", - "dateStarted": "2022-07-29T19:21:06+0000", - "dateFinished": "2022-07-29T19:21:06+0000", - "status": "FINISHED", - "$$hashKey": "object:53" - }, - { - "title": "ESA Features for a long text on stocks and the Fed using the Wikipedia model", - "text": "%sql\n\nSELECT S.FEATURE_ID, S.VALUE FROM\n (SELECT FEATURE_SET(WIKI_MODEL, 10 USING *) FSET FROM \n (SELECT \n 'The more things change... Yes, I''m inclined to agree, especially with regards to the historical relationship between stock prices and bond yields. The two have generally traded together, rising during periods of economic growth and falling during periods of contraction. Consider the period from 1998 through 2010, during which the U.S. economy experienced two expansions as well as two recessions: Then central banks came to the rescue. Fed Chairman Ben Bernanke led from Washington with the help of the bank''s current $3.6T balance sheet. He''s accompanied by Mario Draghi at the European Central Bank and an equally forthright Shinzo Abe in Japan. Their coordinated monetary expansion has provided all the sugar needed for an equities moonshot, while they vowed to hold global borrowing costs at record lows' AS TEXT FROM DUAL)) T,\nTABLE(T.FSET) S ORDER BY S.VALUE DESC", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:06+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "FEATURE_ID": "string", - "VALUE": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "FEATURE_ID\tVALUE\nBen Bernanke\t0.17064524253160657\nRecession\t0.15889239754197812\nMario Draghi\t0.1491065027348536\nCOVID-19 recession\t0.145309094406638\nGreat Recession\t0.1290856902681663\nLong Depression\t0.12204405109050054\nGreat Depression in the United States\t0.11521859419773026\nMonetary policy\t0.1034355579106447\nGreat Recession in the United States\t0.10193175875567674\nGroup of Thirty\t0.09912373068492472\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_438098935", - "id": "20220711-195144_695523427", - "dateCreated": "2021-07-26T18:21:28+0000", - "dateStarted": "2022-07-29T19:21:07+0000", - "dateFinished": "2022-07-29T19:21:07+0000", - "status": "FINISHED", - "$$hashKey": "object:54" - }, - { - "text": "%md\n\n# Comparing Strings for Similarity of Text using the Wikipedia Model\n---\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:07+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

Comparing Strings for Similarity of Text using the Wikipedia Model

\n
\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_-467793705", - "id": "20220711-195144_1345905350", - "dateCreated": "2021-07-26T18:22:12+0000", - "dateStarted": "2022-07-29T19:21:07+0000", - "dateFinished": "2022-07-29T19:21:07+0000", - "status": "FINISHED", - "$$hashKey": "object:55" - }, - { - "title": "Comparison of 'street' vs. 'avenue' using the ESA Wikipedia model", - "text": "%sql\n\n-- FEATURE_COMPARE scoring examples\nSELECT 1-FEATURE_COMPARE(WIKI_MODEL USING 'street' AS TEXT AND USING 'avenue' AS TEXT) \n SIMILARITY FROM DUAL", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:07+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "SIMILARITY": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "SIMILARITY\n0.1936898590428866\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_983089548", - "id": "20220711-195144_1901926621", - "dateCreated": "2021-07-26T18:32:14+0000", - "dateStarted": "2022-07-29T19:21:07+0000", - "dateFinished": "2022-07-29T19:21:07+0000", - "status": "FINISHED", - "$$hashKey": "object:56" - }, - { - "title": "Simple comparison of 'street' vs. 'farm' using the ESA Wikipedia model", - "text": "%sql\n\n-- FEATURE_COMPARE scoring examples\nSELECT 1-FEATURE_COMPARE(WIKI_MODEL USING 'street' AS TEXT AND USING 'farm' AS TEXT) \n SIMILARITY FROM DUAL\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:07+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "SIMILARITY": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "SIMILARITY\n0.007127425352303707\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_-1322858270", - "id": "20220711-195144_1999505675", - "dateCreated": "2021-07-26T18:33:05+0000", - "dateStarted": "2022-07-29T19:21:08+0000", - "dateFinished": "2022-07-29T19:21:08+0000", - "status": "FINISHED", - "$$hashKey": "object:57" - }, - { - "title": "Comparison of two simple texts about Golf using the ESA Wikipedia model", - "text": "%sql\n\nSELECT 1-FEATURE_COMPARE(WIKI_MODEL USING 'There are several PGA tour golfers from South Africa' \n TEXT AND USING 'Nick Price won the 2002 Mastercard Colonial Open' TEXT) \n SIMILARITY FROM DUAL", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:08+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 114.167, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "SIMILARITY": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "SIMILARITY\n0.10969292803597186\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_1251509267", - "id": "20220711-195144_2014732365", - "dateCreated": "2021-07-26T18:34:00+0000", - "dateStarted": "2022-07-29T19:21:08+0000", - "dateFinished": "2022-07-29T19:21:08+0000", - "status": "FINISHED", - "$$hashKey": "object:58" - }, - { - "title": "Comparison of texts about Golf and Football using the ESA Wikipedia model", - "text": "%sql\n\nSELECT 1-FEATURE_COMPARE(WIKI_MODEL USING 'There are several PGA tour golfers from South Africa' \n TEXT AND USING 'John Elway played quarterback for the Denver Broncos' TEXT) \n SIMILARITY FROM DUAL", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:08+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "SIMILARITY": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "SIMILARITY\n0.003917419745909201\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_1190220640", - "id": "20220711-195144_1865388891", - "dateCreated": "2021-07-26T18:34:46+0000", - "dateStarted": "2022-07-29T19:21:08+0000", - "dateFinished": "2022-07-29T19:21:08+0000", - "status": "FINISHED", - "$$hashKey": "object:59" - }, - { - "title": "News on Nasa Rover and SpaceX Moon Gateway using ESA Wikipedia model", - "text": "%sql\n\nSELECT 1-FEATURE_COMPARE(WIKI_MODEL USING \n'NASA Perseverance Mars rover closed in on the red planet after a journey of 293 million miles, hurtling toward a nail-biting seven-minute descent to touchdown Thursday. The mission is an unprecedented attempt to find signs of past microbial life at the site of an ancient martian river, delta and lakebed. Mission managers at NASA Jet Propulsion Laboratory in Pasadena, California, said Wednesday that the spacecraft, still attached to its interplanetary cruise stage, is healthy and flawlessly executing its final approach to Jezero Crater.' AS TEXT\nAND USING \n'NASA has selected SpaceX to deliver the first two segments of the moon-orbiting Gateway space station for its upcoming Artemis program, which aims to put astronauts back on the moon. The elements will launch atop a Falcon Heavy rocket, sometime in 2024. The flight, which is the second to be awarded to SpaceX this week will carry the Gateway''s power and habitation modules. Once deposited in lunar orbit, the Gateway will serve as an outpost for astronauts and equipment heading to the moon as part of NASA Artemis program. Roughly one-sixth the size of the International Space Station, the Gateway will support research investigations, crew, and expeditions to the lunar surface.' AS TEXT) SIMILARITY FROM DUAL", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:08+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 6, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "SIMILARITY": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "SIMILARITY\n0.48847744577133123\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_-1365775010", - "id": "20220711-195144_1991112083", - "dateCreated": "2021-07-26T18:35:33+0000", - "dateStarted": "2022-07-29T19:21:09+0000", - "dateFinished": "2022-07-29T19:21:09+0000", - "status": "FINISHED", - "$$hashKey": "object:60" - }, - { - "title": "News on Nasa Rover and Tennis Naomi Osaka using ESA Wikipedia model", - "text": "%sql\n\nSELECT 1-FEATURE_COMPARE(WIKI_MODEL USING \n'NASA Perseverance Mars rover closed in on the red planet after a journey of 293 million miles, hurtling toward a nail-biting seven-minute descent to touchdown Thursday. The mission is an unprecedented attempt to find signs of past microbial life at the site of an ancient martian river, delta and lakebed. Mission managers at NASA Jet Propulsion Laboratory in Pasadena, California, said Wednesday that the spacecraft, still attached to its interplanetary cruise stage, is healthy and flawlessly executing its final approach to Jezero Crater.' AS TEXT\nAND USING \n'Naomi Osaka, who hasnt lost an official match since last February, put together a dominating performance in the Australian Open semifinals, beating Williams 6-3, 6-4 and ending hopes that the 39-year old American would tie Margaret Court all-time Slam record at this tournament. Osaka, seeking her fourth major title and second Australian Open championship, will play the winner of the second semifinal between American Jennifer Brady, the No. 22 seed, and No. 25 seed Karolina Muchova.' AS TEXT) SIMILARITY FROM DUAL", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:09+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "sql", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/osql", - "fontSize": 9, - "editorHide": true, - "title": true, - "results": { - "0": { - "graph": { - "mode": "table", - "height": 300, - "optionOpen": false, - "setting": { - "table": { - "tableGridState": {}, - "tableColumnTypeState": { - "names": { - "SIMILARITY": "string" - }, - "updated": false - }, - "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", - "tableOptionValue": { - "useFilter": false, - "showPagination": false, - "showAggregationFooter": false - }, - "updated": false, - "initialized": false - } - }, - "commonSetting": {} - } - } - }, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "TABLE", - "data": "SIMILARITY\n0.026660806390262026\n" - } - ] - }, - "apps": [], - "interrupted": false, - "runtimeInfos": {}, - "progressUpdateIntervalMs": 500, - "jobName": "paragraph_1657569104669_-880598145", - "id": "20220711-195144_1900858396", - "dateCreated": "2021-07-26T18:36:12+0000", - "dateStarted": "2022-07-29T19:21:09+0000", - "dateFinished": "2022-07-29T19:21:09+0000", - "status": "FINISHED", - "$$hashKey": "object:61" - }, - { - "text": "%md\n\n# End of Script\n", - "user": "OMLUSER", - "dateUpdated": "2022-07-29T19:21:09+0000", - "progress": 0, - "config": { - "editorSetting": { - "language": "md", - "editOnDblClick": false - }, - "colWidth": 12, - "editorMode": "ace/mode/markdown", - "fontSize": 9, - "editorHide": true, - "results": {}, - "enabled": true - }, - "settings": { - "params": {}, - "forms": {} - }, - "results": { - "code": "SUCCESS", - "msg": [ - { - "type": "HTML", - "data": "

End of Script

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Oracle Machine Learning Datastore in Autonomous Database

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Oracle Machine Learning provides datastores to save your native R or Python objects such as ML models and lists, as well as OML4R or OML4Py proxy objects in your Oracle Database or Autonomous Database instance for use in embedded execution and access across database sessions.

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\n

Copyright (c) 2022 Oracle Corporation

\n
The Universal Permissive License (UPL), Version 1.0
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Initialize interpreters for R and Python and create native model objects

\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-1957419806", + "id": "20221011-180410_326909485", + "dateCreated": "2022-10-07T19:33:33+0000", + "dateStarted": "2022-10-11T18:08:35+0000", + "dateFinished": "2022-10-11T18:08:36+0000", + "status": "FINISHED", + "focus": true, + "$$hashKey": "object:41" + }, + { + "title": "Import OML4R 'ORE' package and create an in-database machine learning model", + "text": "%r\n\nlibrary(ORE) \nore.sync(table = 'IRIS_R') \n\nglm.mod <- ore.odmGLM(Petal.Length~., IRIS_R) \nsummary(glm.mod)\n\n", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:08:36+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "graph": { + "mode": "table", + "height": 300, + "optionOpen": false, + "keys": [], + "values": [], + "groups": [], + "scatter": {} + }, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TEXT", + "data": "\nCall:\nore.odmGLM(formula = Petal.Length ~ ., data = IRIS_R)\n\nResiduals:\n Min 1Q Median 3Q Max \n-0.78396 -0.15708 0.00193 0.14730 0.65418 \n\nCoefficients:\n Estimate Std. Error t value Pr(>|t|) \n(Intercept) -1.11099 0.26987 -4.117 6.45e-05 ***\nSepal.Length 0.60801 0.05024 12.101 < 2e-16 ***\nSepal.Width -0.18052 0.08036 -2.246 0.0262 * \nPetal.Width 0.60222 0.12144 4.959 1.97e-06 ***\nSpeciesversicolor 1.46337 0.17345 8.437 3.14e-14 ***\nSpeciesvirginica 1.97422 0.24480 8.065 2.60e-13 ***\n---\nSignif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n\nResidual standard error: 0.2627 on 144 degrees of freedom\nMultiple R-squared: 0.9786,\tAdjusted R-squared: 0.9778 \nF-statistic: 1317 on 5 and 144 DF, p-value: < 2.2e-16\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_800081049", + "id": "20221011-180410_347481396", + "dateCreated": "2022-10-03T02:53:48+0000", + "dateStarted": "2022-10-11T18:08:37+0000", + "dateFinished": "2022-10-11T18:08:55+0000", + "status": "FINISHED", + "$$hashKey": "object:42" + }, + { + "title": "Import OML4Py 'oml' package and create an in-database machine learning model", + "text": "%python\n\nimport oml\n\nIRIS_PY = oml.sync(table = \"IRIS_PY\")\n\ntrain_x = IRIS_PY.drop('PETAL_LENGTH')\ntrain_y = IRIS_PY['PETAL_LENGTH']\n\nglm_mod = oml.glm(\"regression\")\nglm_mod = glm_mod.fit(train_x, train_y)\nglm_mod", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:08:55+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TEXT", + "data": "\nAlgorithm Name: Generalized Linear Model\n\nMining Function: REGRESSION\n\nTarget: PETAL_LENGTH\n\nSettings: \n setting name setting value\n0 ALGO_NAME ALGO_GENERALIZED_LINEAR_MODEL\n1 GLMS_CONF_LEVEL .95\n2 GLMS_FTR_GENERATION GLMS_FTR_GENERATION_DISABLE\n3 GLMS_FTR_SELECTION GLMS_FTR_SELECTION_DISABLE\n4 ODMS_DETAILS ODMS_ENABLE\n5 ODMS_MISSING_VALUE_TREATMENT ODMS_MISSING_VALUE_AUTO\n6 ODMS_SAMPLING ODMS_SAMPLING_DISABLE\n7 PREP_AUTO ON\n\nComputed Settings: \n setting name setting value\n0 GLMS_CONV_TOLERANCE .0000050000000000000004\n1 GLMS_NUM_ITERATIONS 30\n2 GLMS_RIDGE_REGRESSION GLMS_RIDGE_REG_DISABLE\n3 GLMS_SOLVER GLMS_SOLVER_CHOL\n\nGlobal Statistics: \n attribute name attribute value\n0 ADJUSTED_R_SQUARE 0.97785\n1 AIC -395.115\n2 COEFF_VAR 6.99114\n3 CONVERGED YES\n4 CORRECTED_TOTAL_DF 149\n5 CORRECTED_TOT_SS 464.325\n6 DEPENDENT_MEAN 3.758\n7 ERROR_DF 144\n8 ERROR_MEAN_SQUARE 0.0690256\n9 ERROR_SUM_SQUARES 9.93968\n10 F_VALUE 1316.57\n11 GMSEP 0.0719153\n12 HOCKING_SP 0.000482696\n13 J_P 0.0717866\n14 MODEL_DF 5\n15 MODEL_F_P_VALUE 0\n16 MODEL_MEAN_SQUARE 90.8771\n17 MODEL_SUM_SQUARES 454.386\n18 NUM_PARAMS 6\n19 NUM_ROWS 150\n20 RANK_DEFICIENCY 0\n21 ROOT_MEAN_SQ 0.262727\n22 R_SQ 0.978593\n23 SBIC -377.051\n24 VALID_COVARIANCE_MATRIX YES\n\nAttributes: \nPETAL_WIDTH\nSEPAL_LENGTH\nSEPAL_WIDTH\nSPECIES\n\nPartition: NO\n\nCoefficients: \n\n attribute name attribute value ... p value significance code\n0 (Intercept) None ... 6.445916e-05 ***\n1 PETAL_WIDTH None ... 1.968679e-06 ***\n2 SEPAL_LENGTH None ... 1.073592e-23 ***\n3 SEPAL_WIDTH None ... 2.619373e-02 *\n4 SPECIES versicolor ... 3.142686e-14 ***\n5 SPECIES virginica ... 2.600021e-13 ***\n\n[6 rows x 7 columns]\n\nSignif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 '\n\nFit Details: \n\n name value\n0 ADJUSTED_R_SQUARE 9.778500e-01\n1 AIC -3.951150e+02\n2 COEFF_VAR 6.991144e+00\n3 CORRECTED_TOTAL_DF 1.490000e+02\n4 CORRECTED_TOT_SS 4.643254e+02\n5 DEPENDENT_MEAN 3.758000e+00\n6 ERROR_DF 1.440000e+02\n7 ERROR_MEAN_SQUARE 6.902558e-02\n8 ERROR_SUM_SQUARES 9.939683e+00\n9 F_VALUE 1.316572e+03\n10 GMSEP 7.191532e-02\n11 HOCKING_SP 4.826963e-04\n12 J_P 7.178660e-02\n13 MODEL_CONVERGED 1.000000e+00\n14 MODEL_DF 5.000000e+00\n15 MODEL_F_P_VALUE 2.879219e-118\n16 MODEL_MEAN_SQUARE 9.087714e+01\n17 MODEL_SUM_SQUARES 4.543857e+02\n18 NUM_PARAMS 6.000000e+00\n19 NUM_ROWS 1.500000e+02\n20 RANK_DEFICIENCY 0.000000e+00\n21 ROOT_MEAN_SQ 2.627272e-01\n22 R_SQ 9.785933e-01\n23 SBIC -3.770512e+02\n24 VALID_COVARIANCE_MATRIX 1.000000e+00\n\nRank: \n\n6\n\nDeviance: \n\n9.939683\n\nAIC: \n\n-395\n\nNull Deviance: \n\n464.3254\n\nDF Residual: \n\n144.0\n\nDF Null: \n\n149.0\n\nConverged: \n\nTrue\n\n\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_373381864", + "id": "20221011-180410_689531645", + "dateCreated": "2022-10-03T02:54:12+0000", + "dateStarted": "2022-10-11T18:08:56+0000", + "dateFinished": "2022-10-11T18:09:01+0000", + "status": "FINISHED", + "$$hashKey": "object:43" + }, + { + "text": "%md\n---", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:01+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "
\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-1754821012", + "id": "20221011-180410_1365052265", + "dateCreated": "2022-10-10T21:15:31+0000", + "dateStarted": "2022-10-11T18:09:01+0000", + "dateFinished": "2022-10-11T18:09:01+0000", + "status": "FINISHED", + "$$hashKey": "object:44" + }, + { + "title": "Create a native R machine learning model", + "text": "%r\n\nlm.mod <- lm(Petal.Length~Petal.Width, family='binomial', iris) \nsummary(lm.mod)", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:01+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TEXT", + "data": "Warning message:\n“In lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) :\n extra argument ‘family’ will be disregarded”\n\nCall:\nlm(formula = Petal.Length ~ Petal.Width, data = iris, family = \"binomial\")\n\nResiduals:\n Min 1Q Median 3Q Max \n-1.33542 -0.30347 -0.02955 0.25776 1.39453 \n\nCoefficients:\n Estimate Std. Error t value Pr(>|t|) \n(Intercept) 1.08356 0.07297 14.85 <2e-16 ***\nPetal.Width 2.22994 0.05140 43.39 <2e-16 ***\n---\nSignif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n\nResidual standard error: 0.4782 on 148 degrees of freedom\nMultiple R-squared: 0.9271,\tAdjusted R-squared: 0.9266 \nF-statistic: 1882 on 1 and 148 DF, p-value: < 2.2e-16\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_711262739", + "id": "20221011-180410_597875257", + "dateCreated": "2022-10-10T21:15:13+0000", + "dateStarted": "2022-10-11T18:09:01+0000", + "dateFinished": "2022-10-11T18:09:01+0000", + "status": "FINISHED", + "$$hashKey": "object:45" + }, + { + "title": "Create a native Python machine learning model", + "text": "%python\n\nfrom sklearn import linear_model\n\niris = IRIS_PY.pull()\n\nX = iris[['PETAL_WIDTH']]\ny = iris[['PETAL_LENGTH']]\n\nlm = linear_model.LinearRegression()\n\nlm_mod = lm.fit(X, y)\n\nprint(lm_mod.intercept_, lm_mod.coef_, lm_mod.score(X, y))\n", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:01+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TEXT", + "data": "[1.08355803] [[2.2299405]] 0.9271098389904927\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1236589925", + "id": "20221011-180410_110675196", + "dateCreated": "2022-10-10T21:20:24+0000", + "dateStarted": "2022-10-11T18:09:02+0000", + "dateFinished": "2022-10-11T18:09:02+0000", + "status": "FINISHED", + "$$hashKey": "object:46" + }, + { + "text": "%md\n\n## Save model objects in a datastore\n", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:02+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "

Save model objects in a datastore

\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-491186633", + "id": "20221011-180410_1681135696", + "dateCreated": "2022-10-07T19:33:11+0000", + "dateStarted": "2022-10-11T18:09:02+0000", + "dateFinished": "2022-10-11T18:09:02+0000", + "status": "FINISHED", + "$$hashKey": "object:47" + }, + { + "title": "Save Model and Objects into datastore in R", + "text": "%r\n\nore.save(glm.mod, lm.mod, name = \"ds-r-1\", overwrite = TRUE)\n\nlist <- list(a = 1, b = TRUE, c = \"hoopsa\")\n\nore.save(list, name = \"ds-r-1\", append = TRUE)", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:02+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1509679628", + "id": "20221011-180410_1569411580", + "dateCreated": "2022-10-03T02:54:21+0000", + "dateStarted": "2022-10-11T18:09:02+0000", + "dateFinished": "2022-10-11T18:09:05+0000", + "status": "FINISHED", + "$$hashKey": "object:48" + }, + { + "title": "Save Model and Objects into datastore in Python", + "text": "%python\n\noml.ds.save(objs={'glm_mod': glm_mod, 'lm_mod': lm_mod}, name=\"ds-py-1\", overwrite=True)\n\ndict ={'a':1, 'b': True, 'c': \"hoopsa\"}\n\noml.ds.save(objs={'list': dict}, name=\"ds-py-1\", append=True)", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:05+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1135521586", + "id": "20221011-180410_1758276454", + "dateCreated": "2022-10-03T02:54:36+0000", + "dateStarted": "2022-10-11T18:09:05+0000", + "dateFinished": "2022-10-11T18:09:08+0000", + "status": "FINISHED", + "$$hashKey": "object:49" + }, + { + "text": "%md\n\n## List and view contents of datastores", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:08+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "

List and view contents of datastores

\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-2048060312", + "id": "20221011-180410_674409895", + "dateCreated": "2022-10-07T19:35:27+0000", + "dateStarted": "2022-10-11T18:09:08+0000", + "dateFinished": "2022-10-11T18:09:08+0000", + "status": "FINISHED", + "$$hashKey": "object:50" + }, + { + "title": "List datastore details using R", + "text": "%r\n\nore.datastore(\"ds-r-1\")", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:08+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "\n\n\n\t\n\t\n\n\n\t\n\n
A data.frame: 1 x 5
datastore.nameobject.countsizecreation.datedescription
<chr><dbl><dbl><dttm><chr>
ds-r-13291682022-10-11 18:09:02NA
\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_216894037", + "id": "20221011-180410_1811994217", + "dateCreated": "2022-10-03T02:57:22+0000", + "dateStarted": "2022-10-11T18:09:08+0000", + "dateFinished": "2022-10-11T18:09:08+0000", + "status": "FINISHED", + "$$hashKey": "object:51" + }, + { + "title": "List datastore details using Python", + "text": "%python\n\noml.ds.dir(name=\"ds-py-1\")", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:08+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": { + "0": { + "graph": { + "mode": "table", + "height": 134.534, + "optionOpen": false + } + } + }, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TEXT", + "data": " datastore_name object_count size date description\n0 ds-py-1 3 4367 2022-10-11 18:09:05 None\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1020999520", + "id": "20221011-180410_1803775652", + "dateCreated": "2022-10-03T02:58:04+0000", + "dateStarted": "2022-10-11T18:09:08+0000", + "dateFinished": "2022-10-11T18:09:08+0000", + "status": "FINISHED", + "$$hashKey": "object:52" + }, + { + "text": "%md\n---\n", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:08+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "
\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_874032002", + "id": "20221011-180410_1788149417", + "dateCreated": "2022-10-07T19:36:28+0000", + "dateStarted": "2022-10-11T18:09:09+0000", + "dateFinished": "2022-10-11T18:09:09+0000", + "status": "FINISHED", + "$$hashKey": "object:53" + }, + { + "title": "View datastore contents using R", + "text": "%r\n\nore.datastoreSummary(\"ds-r-1\")", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:09+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "\n\n\n\t\n\t\n\n\n\t\n\t\n\t\n\n
A data.frame: 3 x 6
object.nameclasssizelengthrow.countcol.count
<chr><chr><dbl><dbl><dbl><dbl>
glm.modore.odmGLM1237726NANA
list list 132 3NANA
lm.mod lm 1665912NANA
\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-494439058", + "id": "20221011-180410_1475754441", + "dateCreated": "2022-10-03T02:58:17+0000", + "dateStarted": "2022-10-11T18:09:09+0000", + "dateFinished": "2022-10-11T18:09:10+0000", + "status": "FINISHED", + "$$hashKey": "object:54" + }, + { + "title": "View datastore contents using Python", + "text": "%python\n\noml.ds.describe(name = \"ds-py-1\")", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:10+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TEXT", + "data": " object_name class size length row_count col_count\n0 glm_mod oml.glm 3723 1 1 1\n1 list dict 40 3 1 3\n2 lm_mod LinearRegression 604 1 1 1\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-420363252", + "id": "20221011-180410_1026498240", + "dateCreated": "2022-10-03T02:58:29+0000", + "dateStarted": "2022-10-11T18:09:10+0000", + "dateFinished": "2022-10-11T18:09:10+0000", + "status": "FINISHED", + "$$hashKey": "object:55" + }, + { + "text": "%md\n---\n", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:10+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "
\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_907849927", + "id": "20221011-180410_1294573967", + "dateCreated": "2022-10-07T19:36:53+0000", + "dateStarted": "2022-10-11T18:09:10+0000", + "dateFinished": "2022-10-11T18:09:10+0000", + "status": "FINISHED", + "$$hashKey": "object:56" + }, + { + "title": "View R datastore contents using SQL", + "text": "%sql\n\nselect OBJNAME, CLASS from ALL_RQ_DATASTORE_CONTENTS where DSNAME = 'ds-r-1';", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:10+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/osql", + "fontSize": 9, + "title": true, + "results": { + "0": { + "graph": { + "mode": "table", + "height": 300, + "optionOpen": false, + "setting": { + "table": { + "tableGridState": {}, + "tableColumnTypeState": { + "names": { + "OBJNAME": "string", + "CLASS": "string" + }, + "updated": false + }, + "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", + "tableOptionValue": { + "useFilter": false, + "showPagination": false, + "showAggregationFooter": false + }, + "updated": false, + "initialized": false + } + }, + "commonSetting": {} + } + } + }, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TABLE", + "data": "OBJNAME\tCLASS\nglm.mod\tore.odmGLM\nlist\tlist\nlm.mod\tlm\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1256967390", + "id": "20221011-180410_8744757", + "dateCreated": "2022-10-03T02:58:40+0000", + "dateStarted": "2022-10-11T18:09:10+0000", + "dateFinished": "2022-10-11T18:09:13+0000", + "status": "FINISHED", + "$$hashKey": "object:57" + }, + { + "title": "View Python datastore contents using SQL", + "text": "%sql\n\nselect OBJNAME, CLASS from ALL_PYQ_DATASTORE_CONTENTS where DSNAME = 'ds-py-1';", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:14+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/osql", + "fontSize": 9, + "title": true, + "results": { + "0": { + "graph": { + "mode": "table", + "height": 300, + "optionOpen": false, + "setting": { + "table": { + "tableGridState": {}, + "tableColumnTypeState": { + "names": { + "OBJNAME": "string", + "CLASS": "string" + }, + "updated": false + }, + "tableOptionSpecHash": "[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]", + "tableOptionValue": { + "useFilter": false, + "showPagination": false, + "showAggregationFooter": false + }, + "updated": false, + "initialized": false + } + }, + "commonSetting": {} + } + } + }, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "TABLE", + "data": "OBJNAME\tCLASS\nglm_mod\toml.glm\nlist\tdict\nlm_mod\tLinearRegression\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-2134998665", + "id": "20221011-180410_1717249693", + "dateCreated": "2022-10-03T02:58:59+0000", + "dateStarted": "2022-10-11T18:09:14+0000", + "dateFinished": "2022-10-11T18:09:14+0000", + "status": "FINISHED", + "$$hashKey": "object:58" + }, + { + "text": "%md\n\n## Load datastore objects into memory", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:14+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "

Load datastore objects into memory

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Error t value Pr(>|t|) \n(Intercept) -1.11099 0.26987 -4.117 6.45e-05 ***\nSepal.Length 0.60801 0.05024 12.101 < 2e-16 ***\nSepal.Width -0.18052 0.08036 -2.246 0.0262 * \nPetal.Width 0.60222 0.12144 4.959 1.97e-06 ***\nSpeciesversicolor 1.46337 0.17345 8.437 3.14e-14 ***\nSpeciesvirginica 1.97422 0.24480 8.065 2.60e-13 ***\n---\nSignif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n\nResidual standard error: 0.2627 on 144 degrees of freedom\nMultiple R-squared: 0.9786,\tAdjusted R-squared: 0.9778 \nF-statistic: 1317 on 5 and 144 DF, p-value: < 2.2e-16\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-1230574619", + "id": "20221011-180410_726801076", + "dateCreated": "2022-10-10T21:33:43+0000", + "dateStarted": "2022-10-11T18:09:20+0000", + "dateFinished": "2022-10-11T18:09:20+0000", + "status": "FINISHED", + "$$hashKey": "object:63" + }, + { + "title": "Summarize loaded OML4Py 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GLMS_CONV_TOLERANCE .0000050000000000000004\n1 GLMS_NUM_ITERATIONS 30\n2 GLMS_RIDGE_REGRESSION GLMS_RIDGE_REG_DISABLE\n3 GLMS_SOLVER GLMS_SOLVER_CHOL\n\nGlobal Statistics: \n attribute name attribute value\n0 ADJUSTED_R_SQUARE 0.97785\n1 AIC -395.115\n2 COEFF_VAR 6.99114\n3 CONVERGED YES\n4 CORRECTED_TOTAL_DF 149\n5 CORRECTED_TOT_SS 464.325\n6 DEPENDENT_MEAN 3.758\n7 ERROR_DF 144\n8 ERROR_MEAN_SQUARE 0.0690256\n9 ERROR_SUM_SQUARES 9.93968\n10 F_VALUE 1316.57\n11 GMSEP 0.0719153\n12 HOCKING_SP 0.000482696\n13 J_P 0.0717866\n14 MODEL_DF 5\n15 MODEL_F_P_VALUE 0\n16 MODEL_MEAN_SQUARE 90.8771\n17 MODEL_SUM_SQUARES 454.386\n18 NUM_PARAMS 6\n19 NUM_ROWS 150\n20 RANK_DEFICIENCY 0\n21 ROOT_MEAN_SQ 0.262727\n22 R_SQ 0.978593\n23 SBIC -377.051\n24 VALID_COVARIANCE_MATRIX YES\n\nAttributes: \nPETAL_WIDTH\nSEPAL_LENGTH\nSEPAL_WIDTH\nSPECIES\n\nPartition: NO\n\nCoefficients: \n\n attribute name attribute value ... p value significance code\n0 (Intercept) None ... 6.445916e-05 ***\n1 PETAL_WIDTH None ... 1.968679e-06 ***\n2 SEPAL_LENGTH None ... 1.073592e-23 ***\n3 SEPAL_WIDTH None ... 2.619373e-02 *\n4 SPECIES versicolor ... 3.142686e-14 ***\n5 SPECIES virginica ... 2.600021e-13 ***\n\n[6 rows x 7 columns]\n\nSignif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 '\n\nFit Details: \n\n name value\n0 ADJUSTED_R_SQUARE 9.778500e-01\n1 AIC -3.951150e+02\n2 COEFF_VAR 6.991144e+00\n3 CORRECTED_TOTAL_DF 1.490000e+02\n4 CORRECTED_TOT_SS 4.643254e+02\n5 DEPENDENT_MEAN 3.758000e+00\n6 ERROR_DF 1.440000e+02\n7 ERROR_MEAN_SQUARE 6.902558e-02\n8 ERROR_SUM_SQUARES 9.939683e+00\n9 F_VALUE 1.316572e+03\n10 GMSEP 7.191532e-02\n11 HOCKING_SP 4.826963e-04\n12 J_P 7.178660e-02\n13 MODEL_CONVERGED 1.000000e+00\n14 MODEL_DF 5.000000e+00\n15 MODEL_F_P_VALUE 2.879219e-118\n16 MODEL_MEAN_SQUARE 9.087714e+01\n17 MODEL_SUM_SQUARES 4.543857e+02\n18 NUM_PARAMS 6.000000e+00\n19 NUM_ROWS 1.500000e+02\n20 RANK_DEFICIENCY 0.000000e+00\n21 ROOT_MEAN_SQ 2.627272e-01\n22 R_SQ 9.785933e-01\n23 SBIC 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Delete datastores and datastore contents

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A data.frame: 2 x 6
object.nameclasssizelengthrow.countcol.count
<chr><chr><dbl><dbl><dbl><dbl>
list list 132 3NANA
lm.modlm 1665912NANA
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Grant and revoke access privileges on datastores

\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_379100453", + "id": "20221011-180410_1427284547", + "dateCreated": "2022-10-07T19:39:23+0000", + "dateStarted": "2022-10-11T18:09:29+0000", + "dateFinished": "2022-10-11T18:09:29+0000", + "status": "FINISHED", + "$$hashKey": "object:80" + }, + { + "title": "Grant datastore access to a user in R", + "text": "%r\n\nore.save(glm.mod, \n name = 'ds-r-glm-mod', \n grantable = TRUE, \n overwrite = TRUE)\n\nore.grant('ds-r-glm-mod', type = 'datastore', user = 'OMLUSER2')", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:29+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_-317606835", + "id": "20221011-180410_848852086", + "dateCreated": "2022-10-03T03:02:03+0000", + "dateStarted": "2022-10-11T18:09:29+0000", + "dateFinished": "2022-10-11T18:09:29+0000", + "status": "FINISHED", + "$$hashKey": "object:81" + }, + { + "title": "Grant datastore access to a user in Python", + "text": "%python\n\noml.ds.save(objs={'glm_mod': glm_mod}, \n name= 'ds-py-glm-mod', \n grantable = True, \n overwrite = True)\n\noml.grant(name='ds-py-glm-mod', typ='datastore', user='OMLUSER2')", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:30+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1713023437", + "id": "20221011-180410_1260714506", + "dateCreated": "2022-10-03T03:02:14+0000", + "dateStarted": "2022-10-11T18:09:30+0000", + "dateFinished": "2022-10-11T18:09:31+0000", + "status": "FINISHED", + "$$hashKey": "object:82" + }, + { + "text": "%md\n---", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:31+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "
\n" + } + ] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1302635853", + "id": "20221011-180410_1523630365", + "dateCreated": "2022-10-07T19:40:38+0000", + "dateStarted": "2022-10-11T18:09:31+0000", + "dateFinished": "2022-10-11T18:09:31+0000", + "status": "FINISHED", + "$$hashKey": "object:83" + }, + { + "title": "Revoke datastore access to a user in R", + "text": "%r\n\nore.revoke('ds-r-glm-mod', type = 'datastore', user = 'OMLUSER2')", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:31+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_195848255", + "id": "20221011-180410_437280958", + "dateCreated": "2022-10-03T03:02:24+0000", + "dateStarted": "2022-10-11T18:09:31+0000", + "dateFinished": "2022-10-11T18:09:31+0000", + "status": "FINISHED", + "$$hashKey": "object:84" + }, + { + "title": "Revoke datastore access to a user in Python", + "text": "%python\n\noml.revoke(name = 'ds-py-glm-mod', typ='datastore', user='OMLUSER2')", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:31+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "sql", + "editOnDblClick": false + }, + "colWidth": 6, + "editorMode": "ace/mode/undefined", + "fontSize": 9, + "title": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [] + }, + "apps": [], + "interrupted": false, + "runtimeInfos": {}, + "progressUpdateIntervalMs": 500, + "jobName": "paragraph_1665511450265_1916066867", + "id": "20221011-180410_1801100366", + "dateCreated": "2022-10-03T03:02:33+0000", + "dateStarted": "2022-10-11T18:09:32+0000", + "dateFinished": "2022-10-11T18:09:32+0000", + "status": "FINISHED", + "$$hashKey": "object:85" + }, + { + "text": "%md\n\n# End of script\n", + "user": "OMLUSER", + "dateUpdated": "2022-10-11T18:09:32+0000", + "progress": 0, + "config": { + "editorSetting": { + "language": "md", + "editOnDblClick": false + }, + "colWidth": 12, + "editorMode": "ace/mode/markdown", + "fontSize": 9, + "editorHide": true, + "results": {}, + "enabled": true + }, + "settings": { + "params": {}, + "forms": {} + }, + "results": { + "code": "SUCCESS", + "msg": [ + { + "type": "HTML", + "data": "

End of script

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