impute wrapper without parameter set? #804
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giuseppec
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SteveBronder
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Oct 12, 2016
fixed broken link in README updated NEWS for PR#1026 remove .S3methods import (mlr-org#1216) update auto-generated documentation [ci skip] removed unused variables (mlr-org#1215) updated README benchmark: better arg handling (mlr-org#1224) NEWS xgboost: better handling of arg 'missing' (mlr-org#1225) set default of shw.missing.values to TRUE (mlr-org#1223) * set default to FALSE, identical to ParamHelpers * TRUE TRUE TRUE remove deprecated call and catch warning in mape (mlr-org#1228) fix mlr-org#804 replace preproc with imputed (mlr-org#1231) 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 (mlr-org#1234) * fix xgboost tests * fix more tests test for xgboost printer Add support for visualizing tasks with 2 or more hyperparameters (mlr-org#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 mlr-org#1233 remove weight.fun in place of expanded fun in generatePartialDependence (mlr-org#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 mlr-org#1235 update auto-generated documentation [ci skip] Update description with mason (mlr-org#1237) travis does not work with rdevel, i will open an issue Added ctb (mlr-org#1242) * Added Bruno Vieira as ctb. * Added Bruno Vieira as ctb. fixes for issue mlr-org#63 in the tutorial (mlr-org#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 (mlr-org#1245) * Update RLearner_classif_xgboost.R * Update RLearner_regr_xgboost.R NEWS for mlr-org#1245 and add xgboost version number requirements forgot space... ksvm mini tunable fix for hyper par settings (mlr-org#1249) New measures: Cohen's Kappa and Mean Quadratic Weighted Kappa (mlr-org#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 mlr-org#1250 fixed broken url listLearners output as S3 class with print (mlr-org#1213) Make hyperparseffect tests faster with less iterations (mlr-org#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. 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) 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
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Hi,
I guess this should be
"classif.randomForest.imputed"or something.The text was updated successfully, but these errors were encountered: