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Created TimeRegrTask and started on Arima Learner
NEWS NEWS: are OK until HERE xgboost: missing: go back to set it NA in mlr xgboost: missing: simply use NULL as default fix xgboost tests (#1234) * fix xgboost tests * fix more tests test for xgboost printer Add support for visualizing tasks with 2 or more hyperparameters (#1233) * Add support for visualizing tasks with 2 or more hyperparameters * Add tests for partial dependence * Edit documentation * Forgot to regenerate documentation * Fixed checks for using partial dependence and minor style fixes * Fix typos in argname * Fix arg name in test NEWS for #1233 remove weight.fun in place of expanded fun in generatePartialDependence (#1235) * remove weight.fun in place of expanded fun in generatePartialDependence - internal wrapper for fun arg to allow passing of internal newdata (prediction grid) and data (training data from input arg) which allows computation of weights in fun instead of via an extra step using another arg, weight.fun (now removed) * fix typo NEWS for #1235 update auto-generated documentation [ci skip] Update description with mason (#1237) travis does not work with rdevel, i will open an issue Added ctb (#1242) * Added Bruno Vieira as ctb. * Added Bruno Vieira as ctb. fixes for issue #63 in the tutorial (#1243) - incorrect jacobian function in doPartialDerivativeIteratoin - improper fun/fun.wrapper (for weights use) - test added based on tutorial fail - simplified code a bit renamed file for consistency update auto-generated documentation [ci skip] added the colsample_bylevel parameter in the xgboost learners (#1245) * Update RLearner_classif_xgboost.R * Update RLearner_regr_xgboost.R NEWS for #1245 and add xgboost version number requirements forgot space... ksvm mini tunable fix for hyper par settings (#1249) New measures: Cohen's Kappa and Mean Quadratic Weighted Kappa (#1250) * new measure 'mean quadratic weighted kappa' * add note for mqwk * rename objects in test * rename to wk and fix typo in note * yet another typo * rename wk to wkappa * new_measure_cohens_kappa * correct measure ranges NEWS for #1250 fixed broken url listLearners output as S3 class with print (#1213) Make hyperparseffect tests faster with less iterations (#1260) Created TimeRegrTask and started on Arima Learner Added ARMA learner. For now, allowing cl on line 92 of predictLearner (checkPredictLearnerOutput) to be a ts object Predict added for Arima. Prediction now returns the response, but the 'truth' variables is NA, since forecasts do not know the true value at the time of forecast Added new forecast function. Need to figure out why Arima and forecast are not going to the namespace. Fixed forecast to use holdout set, made mase measure Updated namespace to import forecast, then use the method for WrappedModel. Dunno if this meeses with forecast() in the forecast package. Created Windowing description functions and starting adding Windowing instances Created fixed and growing window instances, may not work for horizon > 1. Added window() function, mostly copying resample(). Need to add functions for windowing with aggregation. Added window level to zzz.R, Created checkAggrBeforeWindow function, WindowPrediction, makeWindowPrediction. Fixed growing and fixed windows by using code from caret. Windowing works for arima, should probably do something about n.ahead and horizon being the same thing. Imported forecast to resample, no longer need forecast functions or windows Removed window and forecast functions, removed window from zzz levels Added skip parameter to growing CV and fixed CV so user does not have to run every iteration. had to capitalize L in makeRLearner for Arima Added docs for time components in resample and resampleDesc Added imports from xts and zoo. Added xreg to Arima. Added Lag and Difference preprocess wrapper. Made createLagDiffFeatures a task preprocessor. Changed names of timeReg to ForecastRegr and timeregr to fcregr. Testing Making sure rebase worked. Updates now pass base tests Updated prediction from timereg to forecastreg. Updated README with some examples of using forecasting. Trying to upload caret picture for windowing. Updated readme with examples. Updated readme. Fixed createLagDiffFeatures. But NA's are handled poorly. added bats, ets, garch, nnetr, tbats, and thief. Not tested yet, but garch works. garch now works for resampling. bats, ets, garch, nnetar, tbats are now working. Updated Readme. thief is not working (frowny face) Made pre processing wrapper using LambertW transform Added LambertW to description suggests and updated the readme. Updated lag and diff preproc func for seasonal lag and differences. Untested. Updated lag and diff preproc to have seasonal lags and diffs. Fixed lag diff preproc to include padding and lag lengths for differencing. Updated docs for createLagDiffFeatures Added forecast helper objects and started working on unit test for Arima. Added ARMA learner. For now, allowing cl on line 92 of predictLearner (checkPredictLearnerOutput) to be a ts object Predict added for Arima. Prediction now returns the response, but the 'truth' variables is NA, since forecasts do not know the true value at the time of forecast Added new forecast function. Need to figure out why Arima and forecast are not going to the namespace. Fixed forecast to use holdout set, made mase measure Updated namespace to import forecast, then use the method for WrappedModel. Dunno if this meeses with forecast() in the forecast package. Created Windowing description functions and starting adding Windowing instances Created fixed and growing window instances, may not work for horizon > 1. Added window() function, mostly copying resample(). Need to add functions for windowing with aggregation. Added window level to zzz.R, Created checkAggrBeforeWindow function, WindowPrediction, makeWindowPrediction. Fixed growing and fixed windows by using code from caret. Windowing works for arima, should probably do something about n.ahead and horizon being the same thing. Imported forecast to resample, no longer need forecast functions or windows had to capitalize L in makeRLearner for Arima Added Lag and Difference preprocess wrapper. Testing Making sure rebase worked. Updated readme. garch now works for resampling. Added LambertW to description suggests and updated the readme. Fixed lag diff preproc to include padding and lag lengths for differencing. Updated docs for createLagDiffFeatures Fixed training for fcregr tasks to only use subsets. Moved test for bats to testthat. Added tests for tbats and ets Added test for createLagDiffFeatures Moved thief to to-do and implimented arfima with a test. Added se prediction type to arfima, bats, ets, nnetar, and tbats Created TimeRegrTask and started on Arima Learner Added ARMA learner. For now, allowing cl on line 92 of predictLearner (checkPredictLearnerOutput) to be a ts object Prediction now returns the response, but the 'truth' variables is NA, since forecasts do not know the true value at the time of forecast Added new forecast function. Need to figure out why Arima and forecast are not going to the namespace. Updated namespace to import forecast, then use the method for WrappedModel. Dunno if this meeses with forecast() in the forecast package. Created fixed and growing window instances, may not work for horizon > 1. Added window() function, mostly copying resample(). Need to add functions for windowing with aggregation. Added window level to zzz.R, Created checkAggrBeforeWindow function, WindowPrediction, makeWindowPrediction. Fixed growing and fixed windows by using code from caret. Windowing works for arima, should probably do something about n.ahead and horizon being the same thing. Imported forecast to resample, no longer need forecast functions or windows Removed window and forecast functions, removed window from zzz levels had to capitalize L in makeRLearner for Arima Added imports from xts and zoo. Added xreg to Arima. Added Lag and Difference preprocess wrapper. Made createLagDiffFeatures a task preprocessor. Changed names of timeReg to ForecastRegr and timeregr to fcregr. Testing Making sure rebase worked. Updates now pass base tests Updated prediction from timereg to forecastreg. Updated README with some examples of using forecasting. Trying to upload caret picture for windowing. Fixed createLagDiffFeatures. But NA's are handled poorly. added bats, ets, garch, nnetr, tbats, and thief. Not tested yet, but garch works. garch now works for resampling. bats, ets, garch, nnetar, tbats are now working. Updated Readme. thief is not working (frowny face) Made pre processing wrapper using LambertW transform Added LambertW to description suggests and updated the readme. Updated lag and diff preproc func for seasonal lag and differences. Untested. Fixed lag diff preproc to include padding and lag lengths for differencing. Updated docs for createLagDiffFeatures Added forecast helper objects and started working on unit test for Arima. Added ARMA learner. For now, allowing cl on line 92 of predictLearner (checkPredictLearnerOutput) to be a ts object Predict added for Arima. Prediction now returns the response, but the 'truth' variables is NA, since forecasts do not know the true value at the time of forecast Added new forecast function. Need to figure out why Arima and forecast are not going to the namespace. Fixed forecast to use holdout set, made mase measure Updated namespace to import forecast, then use the method for WrappedModel. Dunno if this meeses with forecast() in the forecast package. Created Windowing description functions and starting adding Windowing instances Created fixed and growing window instances, may not work for horizon > 1. Added window() function, mostly copying resample(). Need to add functions for windowing with aggregation. Added window level to zzz.R, Created checkAggrBeforeWindow function, WindowPrediction, makeWindowPrediction. Fixed growing and fixed windows by using code from caret. Windowing works for arima, should probably do something about n.ahead and horizon being the same thing. Imported forecast to resample, no longer need forecast functions or windows Removed window and forecast functions, removed window from zzz levels Added skip parameter to growing CV and fixed CV so user does not have to run every iteration. had to capitalize L in makeRLearner for Arima Added imports from xts and zoo. Added xreg to Arima. Added Lag and Difference preprocess wrapper. Made createLagDiffFeatures a task preprocessor. Changed names of timeReg to ForecastRegr and timeregr to fcregr. Testing Making sure rebase worked. Updates now pass base tests Updated prediction from timereg to forecastreg. Updated README with some examples of using forecasting. Updated readme. Fixed createLagDiffFeatures. But NA's are handled poorly. added bats, ets, garch, nnetr, tbats, and thief. Not tested yet, but garch works. garch now works for resampling. bats, ets, garch, nnetar, tbats are now working. Updated Readme. thief is not working (frowny face) Added LambertW to description suggests and updated the readme. Updated lag and diff preproc func for seasonal lag and differences. Untested. Updated lag and diff preproc to have seasonal lags and diffs. Fixed lag diff preproc to include padding and lag lengths for differencing. Updated docs for createLagDiffFeatures Updated merge for Arima prediction. Fixed training for fcregr tasks to only use subsets. Moved test for bats to testthat. Added tests for tbats and ets Added garch unit test. Added test for createLagDiffFeatures Added helper objects for forecast unit testing and Arima can now return standard errors at set levels fixed typo in garch test Moved thief to to-do and implimented arfima with a test. Added se prediction type to arfima, bats, ets, nnetar, and tbats Added updateLearner function and updateModel function to update online models. Added docs for updateModel and built basic test for forecast task. Need to test multiplexer. Fixed Lambert W and created test for forecast Currently passing fcregr and forecast unit tests. Attempted rebase. Changed dates to start with January 14th 1992 Fixed forecast models so that when users want to return quantiles of forecasts they set the predict.type to quantile. Fixed typo in tbats unit test. added fcregr to regression measures. Created test files to run all fcregr models. createLagDiffFeatures had a bug that did not return the target variable which is now resolved. iracing now works with forecast models, but a strange line of code that sets predict length to truth length had to be included. mase moved to measures file. Error found in ets that only happens during test. etsInitialFunc... cannot load from forecast namespace. Created makeForecastRegrLearner function and added checks in predict and train specific to fcregr models. Previously this was done by adding bits to regr tests, but enough has been added to become a new branch. Fixed bugs in growing and fixed resampling where number of iterations was incorrect leading to out of bounds error. added extra params for tbats, bats, and arfima that correspond to auto.arima. Added updateModel to the readme and changed initialWindow to initial.window in docs Updated updateModel to change the task data, but it may not be correct. Changed file name containing updateModel from updateLearner to updateModel. Updated readme to include updating arima model. Updated namespace and docs for updateModel Now passes R CMD CHECK. Update Lambert W transform to not work with one variable and the target predictor. Added frequency to task, updateData and update model have correct documentation. Unit tests for forecast pass, but we need a test for lambertW. Updated data frame conversion for xts s.t. the dates are now in the row names. Added update model functions to bats, ets, nnetar, and tbats. Still need to fix tests for each of those. Fixed lag diff features to work with new data frame conversion of xts. Now in train, if a fcregr has no predictors it will still build the model, which is what we want. built new helpers for updating models. VIP: shifted ... in makeLearner to avoid partial matching feature (feature in quotes). Fixed garch to work with dates being in rownames. Set defaults on nnetar to match forecast's nnetar. Made a test for nnetar Created TimeRegrTask and started on Arima Learner NEWS NEWS: are OK until HERE xgboost: missing: go back to set it NA in mlr xgboost: missing: simply use NULL as default fix xgboost tests (#1234) * fix xgboost tests * fix more tests test for xgboost printer Add support for visualizing tasks with 2 or more hyperparameters (#1233) * Add support for visualizing tasks with 2 or more hyperparameters * Add tests for partial dependence * Edit documentation * Forgot to regenerate documentation * Fixed checks for using partial dependence and minor style fixes * Fix typos in argname * Fix arg name in test NEWS for #1233 remove weight.fun in place of expanded fun in generatePartialDependence (#1235) * remove weight.fun in place of expanded fun in generatePartialDependence - internal wrapper for fun arg to allow passing of internal newdata (prediction grid) and data (training data from input arg) which allows computation of weights in fun instead of via an extra step using another arg, weight.fun (now removed) * fix typo NEWS for #1235 update auto-generated documentation [ci skip] Update description with mason (#1237) travis does not work with rdevel, i will open an issue Added ctb (#1242) * Added Bruno Vieira as ctb. * Added Bruno Vieira as ctb. fixes for issue #63 in the tutorial (#1243) - incorrect jacobian function in doPartialDerivativeIteratoin - improper fun/fun.wrapper (for weights use) - test added based on tutorial fail - simplified code a bit renamed file for consistency update auto-generated documentation [ci skip] added the colsample_bylevel parameter in the xgboost learners (#1245) * Update RLearner_classif_xgboost.R * Update RLearner_regr_xgboost.R NEWS for #1245 and add xgboost version number requirements forgot space... ksvm mini tunable fix for hyper par settings (#1249) New measures: Cohen's Kappa and Mean Quadratic Weighted Kappa (#1250) * new measure 'mean quadratic weighted kappa' * add note for mqwk * rename objects in test * rename to wk and fix typo in note * yet another typo * rename wk to wkappa * new_measure_cohens_kappa * correct measure ranges NEWS for #1250 fixed broken url listLearners output as S3 class with print (#1213) Make hyperparseffect tests faster with less iterations (#1260) Created TimeRegrTask and started on Arima Learner Added ARMA learner. For now, allowing cl on line 92 of predictLearner (checkPredictLearnerOutput) to be a ts object Predict added for Arima. Prediction now returns the response, but the 'truth' variables is NA, since forecasts do not know the true value at the time of forecast Added new forecast function. Need to figure out why Arima and forecast are not going to the namespace. Fixed forecast to use holdout set, made mase measure Updated namespace to import forecast, then use the method for WrappedModel. Dunno if this meeses with forecast() in the forecast package. Created Windowing description functions and starting adding Windowing instances Created fixed and growing window instances, may not work for horizon > 1. Added window() function, mostly copying resample(). Need to add functions for windowing with aggregation. Added window level to zzz.R, Created checkAggrBeforeWindow function, WindowPrediction, makeWindowPrediction. Fixed growing and fixed windows by using code from caret. Windowing works for arima, should probably do something about n.ahead and horizon being the same thing. Imported forecast to resample, no longer need forecast functions or windows Removed window and forecast functions, removed window from zzz levels Added skip parameter to growing CV and fixed CV so user does not have to run every iteration. had to capitalize L in makeRLearner for Arima Added docs for time components in resample and resampleDesc Added imports from xts and zoo. Added xreg to Arima. Added Lag and Difference preprocess wrapper. Made createLagDiffFeatures a task preprocessor. Changed names of timeReg to ForecastRegr and timeregr to fcregr. Testing Making sure rebase worked. Updates now pass base tests Updated prediction from timereg to forecastreg. Updated README with some examples of using forecasting. Trying to upload caret picture for windowing. Updated readme with examples. Updated readme. Fixed createLagDiffFeatures. But NA's are handled poorly. added bats, ets, garch, nnetr, tbats, and thief. Not tested yet, but garch works. garch now works for resampling. bats, ets, garch, nnetar, tbats are now working. Updated Readme. thief is not working (frowny face) Made pre processing wrapper using LambertW transform Added LambertW to description suggests and updated the readme. Updated lag and diff preproc func for seasonal lag and differences. Untested. Updated lag and diff preproc to have seasonal lags and diffs. Fixed lag diff preproc to include padding and lag lengths for differencing. Updated docs for createLagDiffFeatures Added forecast helper objects and started working on unit test for Arima. Added ARMA learner. For now, allowing cl on line 92 of predictLearner (checkPredictLearnerOutput) to be a ts object Predict added for Arima. Prediction now returns the response, but the 'truth' variables is NA, since forecasts do not know the true value at the time of forecast Added new forecast function. Need to figure out why Arima and forecast are not going to the namespace. Fixed forecast to use holdout set, made mase measure Updated namespace to import forecast, then use the method for WrappedModel. Dunno if this meeses with forecast() in the forecast package. Created Windowing description functions and starting adding Windowing instances Created fixed and growing window instances, may not work for horizon > 1. Added window() function, mostly copying resample(). Need to add functions for windowing with aggregation. Added window level to zzz.R, Created checkAggrBeforeWindow function, WindowPrediction, makeWindowPrediction. Fixed growing and fixed windows by using code from caret. Windowing works for arima, should probably do something about n.ahead and horizon being the same thing. Imported forecast to resample, no longer need forecast functions or windows had to capitalize L in makeRLearner for Arima Added Lag and Difference preprocess wrapper. Testing Making sure rebase worked. Updated readme. garch now works for resampling. Added LambertW to description suggests and updated the readme. Fixed lag diff preproc to include padding and lag lengths for differencing. Updated docs for createLagDiffFeatures Fixed training for fcregr tasks to only use subsets. Moved test for bats to testthat. Added tests for tbats and ets Added test for createLagDiffFeatures Moved thief to to-do and implimented arfima with a test. Added se prediction type to arfima, bats, ets, nnetar, and tbats Created TimeRegrTask and started on Arima Learner Added ARMA learner. For now, allowing cl on line 92 of predictLearner (checkPredictLearnerOutput) to be a ts object Prediction now returns the response, but the 'truth' variables is NA, since forecasts do not know the true value at the time of forecast Added new forecast function. Need to figure out why Arima and forecast are not going to the namespace. Updated namespace to import forecast, then use the method for WrappedModel. Dunno if this meeses with forecast() in the forecast package. Created fixed and growing window instances, may not work for horizon > 1. Added window() function, mostly copying resample(). Need to add functions for windowing with aggregation. Added window level to zzz.R, Created checkAggrBeforeWindow function, WindowPrediction, makeWindowPrediction. Fixed growing and fixed windows by using code from caret. Windowing works for arima, should probably do something about n.ahead and horizon being the same thing. Imported forecast to resample, no longer need forecast functions or windows Removed window and forecast functions, removed window from zzz levels had to capitalize L in makeRLearner for Arima Added imports from xts and zoo. Added xreg to Arima. Added Lag and Difference preprocess wrapper. Made createLagDiffFeatures a task preprocessor. Changed names of timeReg to ForecastRegr and timeregr to fcregr. Testing Making sure rebase worked. Updates now pass base tests Updated prediction from timereg to forecastreg. Updated README with some examples of using forecasting. Trying to upload caret picture for windowing. Fixed createLagDiffFeatures. But NA's are handled poorly. added bats, ets, garch, nnetr, tbats, and thief. Not tested yet, but garch works. garch now works for resampling. bats, ets, garch, nnetar, tbats are now working. Updated Readme. thief is not working (frowny face) Made pre processing wrapper using LambertW transform Added LambertW to description suggests and updated the readme. Updated lag and diff preproc func for seasonal lag and differences. Untested. Fixed lag diff preproc to include padding and lag lengths for differencing. Updated docs for createLagDiffFeatures Added forecast helper objects and started working on unit test for Arima. Added ARMA learner. For now, allowing cl on line 92 of predictLearner (checkPredictLearnerOutput) to be a ts object Predict added for Arima. Prediction now returns the response, but the 'truth' variables is NA, since forecasts do not know the true value at the time of forecast Added new forecast function. Need to figure out why Arima and forecast are not going to the namespace. Fixed forecast to use holdout set, made mase measure Updated namespace to import forecast, then use the method for WrappedModel. Dunno if this meeses with forecast() in the forecast package. Created Windowing description functions and starting adding Windowing instances Created fixed and growing window instances, may not work for horizon > 1. Added window() function, mostly copying resample(). Need to add functions for windowing with aggregation. Added window level to zzz.R, Created checkAggrBeforeWindow function, WindowPrediction, makeWindowPrediction. Fixed growing and fixed windows by using code from caret. Windowing works for arima, should probably do something about n.ahead and horizon being the same thing. Imported forecast to resample, no longer need forecast functions or windows Removed window and forecast functions, removed window from zzz levels Added skip parameter to growing CV and fixed CV so user does not have to run every iteration. had to capitalize L in makeRLearner for Arima Added imports from xts and zoo. Added xreg to Arima. Added Lag and Difference preprocess wrapper. Made createLagDiffFeatures a task preprocessor. Changed names of timeReg to ForecastRegr and timeregr to fcregr. Testing Making sure rebase worked. Updates now pass base tests Updated prediction from timereg to forecastreg. Updated README with some examples of using forecasting. Updated readme. Fixed createLagDiffFeatures. But NA's are handled poorly. added bats, ets, garch, nnetr, tbats, and thief. Not tested yet, but garch works. garch now works for resampling. bats, ets, garch, nnetar, tbats are now working. Updated Readme. thief is not working (frowny face) Added LambertW to description suggests and updated the readme. Updated lag and diff preproc func for seasonal lag and differences. Untested. Updated lag and diff preproc to have seasonal lags and diffs. Fixed lag diff preproc to include padding and lag lengths for differencing. Updated docs for createLagDiffFeatures Updated merge for Arima prediction. Fixed training for fcregr tasks to only use subsets. Moved test for bats to testthat. Added tests for tbats and ets Added garch unit test. Added test for createLagDiffFeatures Added helper objects for forecast unit testing and Arima can now return standard errors at set levels fixed typo in garch test Moved thief to to-do and implimented arfima with a test. Added se prediction type to arfima, bats, ets, nnetar, and tbats Added updateLearner function and updateModel function to update online models. Added docs for updateModel and built basic test for forecast task. Need to test multiplexer. Fixed Lambert W and created test for forecast Currently passing fcregr and forecast unit tests. Attempted rebase. Changed dates to start with January 14th 1992 Fixed forecast models so that when users want to return quantiles of forecasts they set the predict.type to quantile. Fixed typo in tbats unit test. added fcregr to regression measures. Created test files to run all fcregr models. createLagDiffFeatures had a bug that did not return the target variable which is now resolved. iracing now works with forecast models, but a strange line of code that sets predict length to truth length had to be included. mase moved to measures file. Error found in ets that only happens during test. etsInitialFunc... cannot load from forecast namespace. Created makeForecastRegrLearner function and added checks in predict and train specific to fcregr models. Previously this was done by adding bits to regr tests, but enough has been added to become a new branch. Fixed bugs in growing and fixed resampling where number of iterations was incorrect leading to out of bounds error. added extra params for tbats, bats, and arfima that correspond to auto.arima. Added updateModel to the readme and changed initialWindow to initial.window in docs Updated updateModel to change the task data, but it may not be correct. Changed file name containing updateModel from updateLearner to updateModel. Updated readme to include updating arima model. Updated namespace and docs for updateModel Now passes R CMD CHECK. Update Lambert W transform to not work with one variable and the target predictor. Added frequency to task, updateData and update model have correct documentation. Unit tests for forecast pass, but we need a test for lambertW. Updated data frame conversion for xts s.t. the dates are now in the row names. Added update model functions to bats, ets, nnetar, and tbats. Still need to fix tests for each of those. Fixed lag diff features to work with new data frame conversion of xts. Now in train, if a fcregr has no predictors it will still build the model, which is what we want. built new helpers for updating models. VIP: shifted ... in makeLearner to avoid partial matching feature (feature in quotes). Fixed garch to work with dates being in rownames. Set defaults on nnetar to match forecast's nnetar. Made a test for nnetar Created TimeRegrTask and started on Arima Learner NEWS NEWS: are OK until HERE xgboost: missing: go back to set it NA in mlr xgboost: missing: simply use NULL as default fix xgboost tests (#1234) * fix xgboost tests * fix more tests test for xgboost printer Add support for visualizing tasks with 2 or more hyperparameters (#1233) * Add support for visualizing tasks with 2 or more hyperparameters * Add tests for partial dependence * Edit documentation * Forgot to regenerate documentation * Fixed checks for using partial dependence and minor style fixes * Fix typos in argname * Fix arg name in test NEWS for #1233 remove weight.fun in place of expanded fun in generatePartialDependence (#1235) * remove weight.fun in place of expanded fun in generatePartialDependence - internal wrapper for fun arg to allow passing of internal newdata (prediction grid) and data (training data from input arg) which allows computation of weights in fun instead of via an extra step using another arg, weight.fun (now removed) * fix typo NEWS for #1235 update auto-generated documentation [ci skip] Update description with mason (#1237) travis does not work with rdevel, i will open an issue Added ctb (#1242) * Added Bruno Vieira as ctb. * Added Bruno Vieira as ctb. fixes for issue #63 in the tutorial (#1243) - incorrect jacobian function in doPartialDerivativeIteratoin - improper fun/fun.wrapper (for weights use) - test added based on tutorial fail - simplified code a bit renamed file for consistency update auto-generated documentation [ci skip] added the colsample_bylevel parameter in the xgboost learners (#1245) * Update RLearner_classif_xgboost.R * Update RLearner_regr_xgboost.R NEWS for #1245 and add xgboost version number requirements forgot space... ksvm mini tunable fix for hyper par settings (#1249) New measures: Cohen's Kappa and Mean Quadratic Weighted Kappa (#1250) * new measure 'mean quadratic weighted kappa' * add note for mqwk * rename objects in test * rename to wk and fix typo in note * yet another typo * rename wk to wkappa * new_measure_cohens_kappa * correct measure ranges NEWS for #1250 fixed broken url listLearners output as S3 class with print (#1213) Make hyperparseffect tests faster with less iterations (#1260) Created TimeRegrTask and started on Arima Learner Added ARMA learner. For now, allowing cl on line 92 of predictLearner (checkPredictLearnerOutput) to be a ts object Predict added for Arima. Prediction now returns the response, but the 'truth' variables is NA, since forecasts do not know the true value at the time of forecast Added new forecast function. Need to figure out why Arima and forecast are not going to the namespace. Fixed forecast to use holdout set, made mase measure Updated namespace to import forecast, then use the method for WrappedModel. Dunno if this meeses with forecast() in the forecast package. Created Windowing description functions and starting adding Windowing instances Created fixed and growing window instances, may not work for horizon > 1. Added window() function, mostly copying resample(). Need to add functions for windowing with aggregation. Added window level to zzz.R, Created checkAggrBeforeWindow function, WindowPrediction, makeWindowPrediction. Fixed growing and fixed windows by using code from caret. Windowing works for arima, should probably do something about n.ahead and horizon being the same thing. Imported forecast to resample, no longer need forecast functions or windows Removed window and forecast functions, removed window from zzz levels Added skip parameter to growing CV and fixed CV so user does not have to run every iteration. had to capitalize L in makeRLearner for Arima Added docs for time components in resample and resampleDesc Added imports from xts and zoo. Added xreg to Arima. Added Lag and Difference preprocess wrapper. Made createLagDiffFeatures a task preprocessor. Changed names of timeReg to ForecastRegr and timeregr to fcregr. Testing Making sure rebase worked. Updates now pass base tests Updated prediction from timereg to forecastreg. Updated README with some examples of using forecasting. Trying to upload caret picture for windowing. Updated readme with examples. Updated readme. Fixed createLagDiffFeatures. But NA's are handled poorly. added bats, ets, garch, nnetr, tbats, and thief. Not tested yet, but garch works. garch now works for resampling. bats, ets, garch, nnetar, tbats are now working. Updated Readme. thief is not working (frowny face) Made pre processing wrapper using LambertW transform Added LambertW to description suggests and updated the readme. Updated lag and diff preproc func for seasonal lag and differences. Untested. Updated lag and diff preproc to have seasonal lags and diffs. Fixed lag diff preproc to include padding and lag lengths for differencing. Updated docs for createLagDiffFeatures Added forecast helper objects and started working on unit test for Arima. Added ARMA learner. For now, allowing cl on line 92 of predictLearner (checkPredictLearnerOutput) to be a ts object Predict added for Arima. Prediction now returns the response, but the 'truth' variables is NA, since forecasts do not know the true value at the time of forecast Added new forecast function. Need to figure out why Arima and forecast are not going to the namespace. Fixed forecast to use holdout set, made mase measure Updated namespace to import forecast, then use the method for WrappedModel. Dunno if this meeses with forecast() in the forecast package. Created Windowing description functions and starting adding Windowing instances Created fixed and growing window instances, may not work for horizon > 1. Added window() function, mostly copying resample(). Need to add functions for windowing with aggregation. Added window level to zzz.R, Created checkAggrBeforeWindow function, WindowPrediction, makeWindowPrediction. Fixed growing and fixed windows by using code from caret. Windowing works for arima, should probably do something about n.ahead and horizon being the same thing. Imported forecast to resample, no longer need forecast functions or windows had to capitalize L in makeRLearner for Arima Added Lag and Difference preprocess wrapper. Testing Making sure rebase worked. Updated readme. garch now works for resampling. Added LambertW to description suggests and updated the readme. Fixed lag diff preproc to include padding and lag lengths for differencing. Updated docs for createLagDiffFeatures Fixed training for fcregr tasks to only use subsets. Moved test for bats to testthat. Added tests for tbats and ets Added test for createLagDiffFeatures Moved thief to to-do and implimented arfima with a test. Added se prediction type to arfima, bats, ets, nnetar, and tbats Created TimeRegrTask and started on Arima Learner Added ARMA learner. For now, allowing cl on line 92 of predictLearner (checkPredictLearnerOutput) to be a ts object Prediction now returns the response, but the 'truth' variables is NA, since forecasts do not know the true value at the time of forecast Added new forecast function. Need to figure out why Arima and forecast are not going to the namespace. Updated namespace to import forecast, then use the method for WrappedModel. Dunno if this meeses with forecast() in the forecast package. Created fixed and growing window instances, may not work for horizon > 1. Added window() function, mostly copying resample(). Need to add functions for windowing with aggregation. Added window level to zzz.R, Created checkAggrBeforeWindow function, WindowPrediction, makeWindowPrediction. Fixed growing and fixed windows by using code from caret. Windowing works for arima, should probably do something about n.ahead and horizon being the same thing. Imported forecast to resample, no longer need forecast functions or windows Removed window and forecast functions, removed window from zzz levels had to capitalize L in makeRLearner for Arima Added imports from xts and zoo. Added xreg to Arima. Added Lag and Difference preprocess wrapper. Made createLagDiffFeatures a task preprocessor. Changed names of timeReg to ForecastRegr and timeregr to fcregr. Testing Making sure rebase worked. Updates now pass base tests Updated prediction from timereg to forecastreg. Updated README with some examples of using forecasting. Trying to upload caret picture for windowing. Fixed createLagDiffFeatures. But NA's are handled poorly. added bats, ets, garch, nnetr, tbats, and thief. Not tested yet, but garch works. garch now works for resampling. bats, ets, garch, nnetar, tbats are now working. Updated Readme. thief is not working (frowny face) Made pre processing wrapper using LambertW transform Added LambertW to description suggests and updated the readme. Updated lag and diff preproc func for seasonal lag and differences. Untested. Fixed lag diff preproc to include padding and lag lengths for differencing. Updated docs for createLagDiffFeatures Added forecast helper objects and started working on unit test for Arima. Added ARMA learner. For now, allowing cl on line 92 of predictLearner (checkPredictLearnerOutput) to be a ts object Predict added for Arima. Prediction now returns the response, but the 'truth' variables is NA, since forecasts do not know the true value at the time of forecast Added new forecast function. Need to figure out why Arima and forecast are not going to the namespace. Fixed forecast to use holdout set, made mase measure Updated namespace to import forecast, then use the method for WrappedModel. Dunno if this meeses with forecast() in the forecast package. Created Windowing description functions and starting adding Windowing instances Created fixed and growing window instances, may not work for horizon > 1. Added window() function, mostly copying resample(). Need to add functions for windowing with aggregation. Added window level to zzz.R, Created checkAggrBeforeWindow function, WindowPrediction, makeWindowPrediction. Fixed growing and fixed windows by using code from caret. Windowing works for arima, should probably do something about n.ahead and horizon being the same thing. Imported forecast to resample, no longer need forecast functions or windows Removed window and forecast functions, removed window from zzz levels Added skip parameter to growing CV and fixed CV so user does not have to run every iteration. had to capitalize L in makeRLearner for Arima Added imports from xts and zoo. Added xreg to Arima. Added Lag and Difference preprocess wrapper. Made createLagDiffFeatures a task preprocessor. Changed names of timeReg to ForecastRegr and timeregr to fcregr. Testing Making sure rebase worked. Updates now pass base tests Updated prediction from timereg to forecastreg. Updated README with some examples of using forecasting. Updated readme. Fixed createLagDiffFeatures. But NA's are handled poorly. added bats, ets, garch, nnetr, tbats, and thief. Not tested yet, but garch works. garch now works for resampling. bats, ets, garch, nnetar, tbats are now working. Updated Readme. thief is not working (frowny face) Added LambertW to description suggests and updated the readme. Updated lag and diff preproc func for seasonal lag and differences. Untested. Updated lag and diff preproc to have seasonal lags and diffs. Fixed lag diff preproc to include padding and lag lengths for differencing. Updated docs for createLagDiffFeatures Updated merge for Arima prediction. Fixed training for fcregr tasks to only use subsets. Moved test for bats to testthat. Added tests for tbats and ets Added garch unit test. Added test for createLagDiffFeatures Added helper objects for forecast unit testing and Arima can now return standard errors at set levels fixed typo in garch test Moved thief to to-do and implimented arfima with a test. Added se prediction type to arfima, bats, ets, nnetar, and tbats Added updateLearner function and updateModel function to update online models. Added docs for updateModel and built basic test for forecast task. Need to test multiplexer. Fixed Lambert W and created test for forecast Currently passing fcregr and forecast unit tests. Attempted rebase. Changed dates to start with January 14th 1992 Fixed forecast models so that when users want to return quantiles of forecasts they set the predict.type to quantile. Fixed typo in tbats unit test. added fcregr to regression measures. Created test files to run all fcregr models. createLagDiffFeatures had a bug that did not return the target variable which is now resolved. iracing now works with forecast models, but a strange line of code that sets predict length to truth length had to be included. mase moved to measures file. Error found in ets that only happens during test. etsInitialFunc... cannot load from forecast namespace. Created makeForecastRegrLearner function and added checks in predict and train specific to fcregr models. Previously this was done by adding bits to regr tests, but enough has been added to become a new branch. Fixed bugs in growing and fixed resampling where number of iterations was incorrect leading to out of bounds error. added extra params for tbats, bats, and arfima that correspond to auto.arima. Added updateModel to the readme and changed initialWindow to initial.window in docs Updated updateModel to change the task data, but it may not be correct. Changed file name containing updateModel from updateLearner to updateModel. Updated readme to include updating arima model. Updated namespace and docs for updateModel Now passes R CMD CHECK. Update Lambert W transform to not work with one variable and the target predictor. Added frequency to task, updateData and update model have correct documentation. Unit tests for forecast pass, but we need a test for lambertW. Updated data frame conversion for xts s.t. the dates are now in the row names. Added update model functions to bats, ets, nnetar, and tbats. Still need to fix tests for each of those. Fixed lag diff features to work with new data frame conversion of xts. Now in train, if a fcregr has no predictors it will still build the model, which is what we want. built new helpers for updating models. VIP: shifted ... in makeLearner to avoid partial matching feature (feature in quotes). Fixed garch to work with dates being in rownames. Set defaults on nnetar to match forecast's nnetar. Made a test for nnetar Created TimeRegrTask and started on Arima Learner NEWS NEWS: are OK until HERE xgboost: missing: go back to set it NA in mlr xgboost: missing: simply use NULL as default fix xgboost tests (#1234) * fix xgboost tests * fix more tests test for xgboost printer Add support for visualizing tasks with 2 or more hyperparameters (#1233) * Add support for visualizing tasks with 2 or more hyperparameters * Add tests for partial dependence * Edit documentation * Forgot to regenerate documentation * Fixed checks for using partial dependence and minor style fixes * Fix typos in argname * Fix arg name in test NEWS for #1233 remove weight.fun in place of expanded fun in generatePartialDependence (#1235) * remove weight.fun in place of expanded fun in generatePartialDependence - internal wrapper for fun arg to allow passing of internal newdata (prediction grid) and data (training data from input arg) which allows computation of weights in fun instead of via an extra step using another arg, weight.fun (now removed) * fix typo NEWS for #1235 update auto-generated documentation [ci skip] Update description with mason (#1237) travis does not work with rdevel, i will open an issue Added ctb (#1242) * Added Bruno Vieira as ctb. * Added Bruno Vieira as ctb. fixes for issue #63 in the tutorial (#1243) - incorrect jacobian function in doPartialDerivativeIteratoin - improper fun/fun.wrapper (for weights use) - test added based on tutorial fail - simplified code a bit renamed file for consistency update auto-generated documentation [ci skip] added the colsample_bylevel parameter in the xgboost learners (#1245) * Update RLearner_classif_xgboost.R * Update RLearner_regr_xgboost.R NEWS for #1245 and add xgboost version number requirements forgot space... ksvm mini tunable fix for hyper par settings (#1249) New measures: Cohen's Kappa and Mean Quadratic Weighted Kappa (#1250) * new measure 'mean quadratic weighted kappa' * add note for mqwk * rename objects in test * rename to wk and fix typo in note * yet another typo * rename wk to wkappa * new_measure_cohens_kappa * correct measure ranges NEWS for #1250 fixed broken url listLearners output as S3 class with print (#1213) Make hyperparseffect tests faster with less iterations (#1260) Created TimeRegrTask and started on Arima Learner Added ARMA learner. For now, allowing cl on line 92 of predictLearner (checkPredictLearnerOutput) to be a ts object Predict added for Arima. Prediction now returns the response, but the 'truth' variables is NA, since forecasts do not know the true value at the time of forecast Added new forecast function. Need to figure out why Arima and forecast are not going to the namespace. Fixed forecast to use holdout set, made mase measure Updated namespace to import forecast, then use the method for WrappedModel. Dunno if this meeses with forecast() in the forecast package. Created Windowing description functions and starting adding Windowing instances Created fixed and growing window instances, may not work for horizon > 1. Added window() function, mostly copying resample(). Need to add functions for windowing with aggregation. Added window level to zzz.R, Created checkAggrBeforeWindow function, WindowPrediction, makeWindowPrediction. Fixed growing and fixed windows by using code from caret. Windowing works for arima, should probably do something about n.ahead and horizon being the same thing. Imported forecast to resample, no longer need forecast functions or windows Removed window and forecast functions, removed window from zzz levels Added skip parameter to growing CV and fixed CV so user does not have to run every iteration. had to capitalize L in makeRLearner for Arima Added docs for time components in resample and resampleDesc Added imports from xts and zoo. Added xreg to Arima. Added Lag and Difference preprocess wrapper. Made createLagDiffFeatures a task preprocessor. Changed names of timeReg to ForecastRegr and timeregr to fcregr. Testing Making sure rebase worked. Updates now pass base tests Updated prediction from timereg to forecastreg. Updated README with some examples of using forecasting. Trying to upload caret picture for windowing. Updated readme with examples. Updated readme. Fixed createLagDiffFeatures. But NA's are handled poorly. added bats, ets, garch, nnetr, tbats, and thief. Not tested yet, but garch works. garch now works for resampling. bats, ets, garch, nnetar, tbats are now working. Updated Readme. thief is not working (frowny face) Made pre processing wrapper using LambertW transform Added LambertW to description suggests and updated the readme. Updated lag and diff preproc func for seasonal lag and differences. Untested. Updated lag and diff preproc to have seasonal lags and diffs. Fixed lag diff preproc to include padding and lag lengths for differencing. Updated docs for createLagDiffFeatures Added forecast helper objects and started working on unit test for Arima. Added ARMA learner. For now, allowing cl on line 92 of predictLearner (checkPredictLearnerOutput) to be a ts object Predict added for Arima. Prediction now returns the response, but the 'truth' variables is NA, since forecasts do not know the true value at the time of forecast Added new forecast function. Need to figure out why Arima and forecast are not going to the namespace. Fixed forecast to use holdout set, made mase measure Updated namespace to import forecast, then use the method for WrappedModel. Dunno if this meeses with forecast() in the forecast package. Created Windowing description functions and starting adding Windowing instances Created fixed and growing window instances, may not work for horizon > 1. Added window() function, mostly copying resample(). Need to add functions for windowing with aggregation. Added window level to zzz.R, Created checkAggrBeforeWindow function, WindowPrediction, makeWindowPrediction. Fixed growing and fixed windows by using code from caret. Windowing works for arima, should probably do something about n.ahead and horizon being the same thing. Imported forecast to resample, no longer need forecast functions or windows had to capitalize L in makeRLearner for Arima Added Lag and Difference preprocess wrapper. Testing Making sure rebase worked. Updated readme. garch now works for resampling. Added LambertW to description suggests and updated the readme. Fixed lag diff preproc to include padding and lag lengths for differencing. Updated docs for createLagDiffFeatures Fixed training for fcregr tasks to only use subsets. Moved test for bats to testthat. Added tests for tbats and ets Added test for createLagDiffFeatures Moved thief to to-do and implimented arfima with a test. Added se prediction type to arfima, bats, ets, nnetar, and tbats Created TimeRegrTask and started on Arima Learner Added ARMA learner. For now, allowing cl on line 92 of predictLearner (checkPredictLearnerOutput) to be a ts object Prediction now returns the response, but the 'truth' variables is NA, since forecasts do not know the true value at the time of forecast Added new forecast function. Need to figure out why Arima and forecast are not going to the namespace. Updated namespace to import forecast, then use the method for WrappedModel. Dunno if this meeses with forecast() in the forecast package. Created fixed and growing window instances, may not work for horizon > 1. Added window() function, mostly copying resample(). Need to add functions for windowing with aggregation. Added window level to zzz.R, Created checkAggrBeforeWindow function, WindowPrediction, makeWindowPrediction. Fixed growing and fixed windows by using code from caret. Windowing works for arima, should probably do something about n.ahead and horizon being the same thing. Imported forecast to resample, no longer need forecast functions or windows Removed window and forecast functions, removed window from zzz levels had to capitalize L in makeRLearner for Arima Added imports from xts and zoo. Added xreg to Arima. Added Lag and Difference preprocess wrapper. Made createLagDiffFeatures a task preprocessor. Changed names of timeReg to ForecastRegr and timeregr to fcregr. Testing Making sure rebase worked. Updates now pass base tests Updated prediction from timereg to forecastreg. Updated README with some examples of using forecasting. Trying to upload caret picture for windowing. Fixed createLagDiffFeatures. But NA's are handled poorly. added bats, ets, garch, nnetr, tbats, and thief. Not tested yet, but garch works. garch now works for resampling. bats, ets, garch, nnetar, tbats are now working. Updated Readme. thief is not working (frowny face) Made pre processing wrapper using LambertW transform Added LambertW to description suggests and updated the readme. Updated lag and diff preproc func for seasonal lag and differences. Untested. Fixed lag diff preproc to include padding and lag lengths for differencing. Updated docs for createLagDiffFeatures Added forecast helper objects and started working on unit test for Arima. Added ARMA learner. For now, allowing cl on line 92 of predictLearner (checkPredictLearnerOutput) to be a ts object Predict added for Arima. Prediction now returns the response, but the 'truth' variables is NA, since forecasts do not know the true value at the time of forecast Added new forecast function. Need to figure out why Arima and forecast are not going to the namespace. Fixed forecast to use holdout set, made mase measure Updated namespace to import forecast, then use the method for WrappedModel. Dunno if this meeses with forecast() in the forecast package. Created Windowing description functions and starting adding Windowing instances Created fixed and growing window instances, may not work for horizon > 1. Added window() function, mostly copying resample(). Need to add functions for windowing with aggregation. Added window level to zzz.R, Created checkAggrBeforeWindow function, WindowPrediction, makeWindowPrediction. Fixed growing and fixed windows by using code from caret. Windowing works for arima, should probably do something about n.ahead and horizon being the same thing. Imported forecast to resample, no longer need forecast functions or windows Removed window and forecast functions, removed window from zzz levels Added skip parameter to growing CV and fixed CV so user does not have to run every iteration. had to capitalize L in makeRLearner for Arima Added imports from xts and zoo. Added xreg to Arima. Added Lag and Difference preprocess wrapper. Made createLagDiffFeatures a task preprocessor. Changed names of timeReg to ForecastRegr and timeregr to fcregr. Testing Making sure rebase worked. Updates now pass base tests Updated prediction from timereg to forecastreg. Updated README with some examples of using forecasting. Updated readme. Fixed createLagDiffFeatures. But NA's are handled poorly. added bats, ets, garch, nnetr, tbats, and thief. Not tested yet, but garch works. garch now works for resampling. bats, ets, garch, nnetar, tbats are now working. Updated Readme. thief is not working (frowny face) Added LambertW to description suggests and updated the readme. Updated lag and diff preproc func for seasonal lag and differences. Untested. Updated lag and diff preproc to have seasonal lags and diffs. Fixed lag diff preproc to include padding and lag lengths for differencing. Updated docs for createLagDiffFeatures Updated merge for Arima prediction. Fixed training for fcregr tasks to only use subsets. Moved test for bats to testthat. Added tests for tbats and ets Added garch unit test. Added test for createLagDiffFeatures Added helper objects for forecast unit testing and Arima can now return standard errors at set levels fixed typo in garch test Moved thief to to-do and implimented arfima with a test. Added se prediction type to arfima, bats, ets, nnetar, and tbats Added updateLearner function and updateModel function to update online models. Added docs for updateModel and built basic test for forecast task. Need to test multiplexer. Fixed Lambert W and created test for forecast Currently passing fcregr and forecast unit tests. Attempted rebase. Changed dates to start with January 14th 1992 Fixed forecast models so that when users want to return quantiles of forecasts they set the predict.type to quantile. Fixed typo in tbats unit test. added fcregr to regression measures. Created test files to run all fcregr models. createLagDiffFeatures had a bug that did not return the target variable which is now resolved. iracing now works with forecast models, but a strange line of code that sets predict length to truth length had to be included. mase moved to measures file. Error found in ets that only happens during test. etsInitialFunc... cannot load from forecast namespace. Created makeForecastRegrLearner function and added checks in predict and train specific to fcregr models. Previously this was done by adding bits to regr tests, but enough has been added to become a new branch. Fixed bugs in growing and fixed resampling where number of iterations was incorrect leading to out of bounds error. added extra params for tbats, bats, and arfima that correspond to auto.arima. Added updateModel to the readme and changed initialWindow to initial.window in docs Updated updateModel to change the task data, but it may not be correct. Changed file name containing updateModel from updateLearner to updateModel. Updated readme to include updating arima model. Updated namespace and docs for updateModel Now passes R CMD CHECK. Update Lambert W transform to not work with one variable and the target predictor. Added frequency to task, updateData and update model have correct documentation. Unit tests for forecast pass, but we need a test for lambertW. Updated data frame conversion for xts s.t. the dates are now in the row names. Added update model functions to bats, ets, nnetar, and tbats. Still need to fix tests for each of those. Fixed lag diff features to work with new data frame conversion of xts. Now in train, if a fcregr has no predictors it will still build the model, which is what we want. built new helpers for updating models. VIP: shifted ... in makeLearner to avoid partial matching feature (feature in quotes). Fixed garch to work with dates being in rownames. Set defaults on nnetar to match forecast's nnetar. Made a test for nnetar Added ggvis and shiny to depends in description else R CMD CHECK was failing. Removed weird file ~HEAD. and updated man for makeLearner. Now we can start with a forecast task, do createLagDiff, and get back a regr task if no cols are selected. This lets us us regr tasks for forecasting. Changed updateData() to updateLagDiff() as that's all I really needed it for. predictLearner now allows fcregr types to have no new data. cleaned up mase in measures. Fixed GrowthCV and FixedCV so they both create initial.window and skip proportional to size. Need to fix lagdiff features. Made some mods to StackedLearner. Updated Readme Added Multivariate forecast type and learner. Performed rebase Passing R CMD CHECK with one note. Added multivariate forecasts, can be done with a stacked learner. updated README. Passing R CMD CHECK. Still need to update docs. Corrected according to style guide, removed extra whitespace and assignment arrows. ggvis and shiny were kept as they are called in zzz. Added packages to description in alphabetical order. Put back in official readme. Removed leftover comma in description suggests Added print statement for multivariate forecast tasks. Added the printing of target variables to forecast and multivariate forecast tasks. Added xreg variables to be non-target variables in forecast task. fixed Arima and auto.arima model update methods. For some reason a <- must be in fun1() for learner.model to be assigned. Fixed some bugs in createLagDiffFeatures. Added arbitrary forecast function. Still need to write tests for forecast Fixed bug to preserve factor levels when making lags of factors. Created new helper objects for forecasting tasks. Made unit tests for forecasting with base tasks. Fixed whitespacing merge issue in helper_learners_all. Updated to aavoid compilation errors. Failing base tests which I have not changed. Reduced memory usage in forecast by only taking necessary data instead of the whole dataset. Added example for lagDiff Fixed lagdiff tests and objects in task that were created for forecast which overwrote base test objects Had to remove xgboost::predict from xgboost as predict is not exported from xgboosts library WARNING: Placed an expect_warning() in classif test for xgboost after receiving a warning obout mulitple objective functions Fixed bugs in forecast functions to work with tests Trying to update travis to use g++ and gcc 6.9 trying to update g++ and gcc to version 6 For now, allowing slightly higer tolerance in difference for update step. Trying to load up gfortran 6 as well. Removing temp travis.yml file Pre-rebase Removed warning from classif_xgboost test copy-paste xgboost classif tests from master Removed spacing from xgboost tests and learners Commented out test on classifiers for travis until DLL error is fixed. Trying out gcDLLs() in learner tests Included properties = 'oneclass' to tests on all classifiers Fixed bug in forecasting for machine learning models where length() was being used instead of nrow() Set tolerance higher for ets Fixed bug in MASE measure Made change to multivar.mase to use ColMeans for speed
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