Package: EnsembleBase 1.0.2
EnsembleBase: Extensible Package for Parallel, Batch Training of Base Learners for Ensemble Modeling
Extensible S4 classes and methods for batch training of regression and classification algorithms such as Random Forest, Gradient Boosting Machine, Neural Network, Support Vector Machines, K-Nearest Neighbors, Penalized Regression (L1/L2), and Bayesian Additive Regression Trees. These algorithms constitute a set of 'base learners', which can subsequently be combined together to form ensemble predictions. This package provides cross-validation wrappers to allow for downstream application of ensemble integration techniques, including best-error selection. All base learner estimation objects are retained, allowing for repeated prediction calls without the need for re-training. For large problems, an option is provided to save estimation objects to disk, along with prediction methods that utilize these objects. This allows users to train and predict with large ensembles of base learners without being constrained by system RAM.
Authors:
EnsembleBase_1.0.2.tar.gz
EnsembleBase_1.0.2.zip(r-4.5)EnsembleBase_1.0.2.zip(r-4.4)EnsembleBase_1.0.2.zip(r-4.3)
EnsembleBase_1.0.2.tgz(r-4.4-any)EnsembleBase_1.0.2.tgz(r-4.3-any)
EnsembleBase_1.0.2.tar.gz(r-4.5-noble)EnsembleBase_1.0.2.tar.gz(r-4.4-noble)
EnsembleBase_1.0.2.tgz(r-4.4-emscripten)EnsembleBase_1.0.2.tgz(r-4.3-emscripten)
EnsembleBase.pdf |EnsembleBase.html✨
EnsembleBase/json (API)
# Install 'EnsembleBase' in R: |
install.packages('EnsembleBase', repos = c('https://asmahani.r-universe.dev', 'https://cloud.r-project.org')) |
- servo - Servo Data Set
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 8 years agofrom:c9a98b3fe0. Checks:OK: 3 NOTE: 4. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Aug 21 2024 |
R-4.5-win | NOTE | Aug 21 2024 |
R-4.5-linux | NOTE | Aug 21 2024 |
R-4.4-win | NOTE | Aug 21 2024 |
R-4.4-mac | NOTE | Aug 21 2024 |
R-4.3-win | OK | Aug 21 2024 |
R-4.3-mac | OK | Aug 21 2024 |
Exports:BaseLearner.Fitextract.baselearner.namegenerate.partitiongenerate.partitionsload.objectmake.configsmake.instancesRegression.Batch.FitRegression.CV.Batch.FitRegression.CV.Fitregression.extract.responseRegression.Integrator.FitRegression.Select.Fitrmse.errorvalidate
Dependencies:bartMachinebartMachineJARsclassclicodetoolscpp11digestdoParalleldoRNGe1071foreachgbmglmnetglueigraphiteratorsitertoolskknnlatticelifecyclemagrittrMASSMatrixmissForestnnetpkgconfigproxyrandomForestRcppRcppEigenrJavarlangrngtoolsshapesurvivalvctrs
Readme and manuals
Help Manual
Help page | Topics |
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Classes '"KNN.Regression.Config"', '"NNET.Regression.Config"', '"RF.Regression.Config"', '"SVM.Regression.Config"', '"GBM.Regression.Config"', '"PENREG.Regression.Config"', '"BART.Regression.Config"' | BART.Regression.Config-class GBM.Regression.Config-class KNN.Regression.Config-class NNET.Regression.Config-class PENREG.Regression.Config-class RF.Regression.Config-class SVM.Regression.Config-class |
Classes '"KNN.Regression.FitObj"', '"NNET.Regression.FitObj"', '"RF.Regression.FitObj"', '"SVM.Regression.FitObj"', '"GBM.Regression.FitObj"', '"PENREG.Regression.FitObj"', '"BART.Regression.FitObj"' | BART.Regression.FitObj-class GBM.Regression.FitObj-class KNN.Regression.FitObj-class NNET.Regression.FitObj-class PENREG.Regression.FitObj-class RF.Regression.FitObj-class SVM.Regression.FitObj-class |
Classes '"BaseLearner.Batch.FitObj"' and '"Regression.Batch.FitObj"' | BaseLearner.Batch.FitObj-class Regression.Batch.FitObj-class |
Classes '"BaseLearner.Config"', '"Regression.Config"' | BaseLearner.Config-class Regression.Config-class |
Classes '"BaseLearner.CV.Batch.FitObj"' and '"Regression.CV.Batch.FitObj"' | BaseLearner.CV.Batch.FitObj-class Regression.CV.Batch.FitObj-class |
Classes '"BaseLearner.CV.FitObj"' and '"Regression.CV.FitObj"' | BaseLearner.CV.FitObj-class Regression.CV.FitObj-class |
Generic S4 Method for Fitting Base Learners | BaseLearner.Fit BaseLearner.Fit,BART.Regression.Config-method BaseLearner.Fit,GBM.Regression.Config-method BaseLearner.Fit,KNN.Regression.Config-method BaseLearner.Fit,NNET.Regression.Config-method BaseLearner.Fit,PENREG.Regression.Config-method BaseLearner.Fit,RF.Regression.Config-method BaseLearner.Fit,SVM.Regression.Config-method BaseLearner.Fit-methods |
Classes '"BaseLearner.FitObj"' and '"Regression.FitObj"' | BaseLearner.FitObj-class Regression.FitObj-class |
Classes '"Instance"' and '"Instance.List"' | Instance-class Instance.List-class |
Helper Functions for Manipulating Base Learner Configurations | extract.baselearner.name make.configs make.configs.bart.regression make.configs.gbm.regression make.configs.knn.regression make.configs.nnet.regression make.configs.penreg.regression make.configs.rf.regression make.configs.svm.regression make.instances |
Class '"OptionalInteger"' | OptionalCharacter-class OptionalInteger-class OptionalNumeric-class |
Batch Training, Prediction and Diagnostics of Regression Base Learners | plot.Regression.Batch.FitObj predict.Regression.Batch.FitObj Regression.Batch.Fit |
CV Batch Training and Diagnostics of Regression Base Learners | plot.Regression.CV.Batch.FitObj predict.Regression.CV.Batch.FitObj Regression.CV.Batch.Fit |
Cross-Validated Training and Prediction of Regression Base Learners | predict.Regression.CV.FitObj Regression.CV.Fit |
Classes '"Regression.Integrator.Config"', '"Regression.Select.Config"', '"Regression.Integrator.FitObj"', '"Regression.Select.FitObj"' | Regression.Integrator.Config-class Regression.Integrator.FitObj-class Regression.Select.Config-class Regression.Select.FitObj-class |
Generic Integrator Methods in Package 'EnsembleBase' | Regression.Integrator.Fit Regression.Integrator.Fit-methods Regression.Select.Fit Regression.Select.Fit-methods |
Class '"RegressionEstObj"' | RegressionEstObj-class |
Class '"RegressionSelectPred"' | RegressionSelectPred-class |
Servo Data Set | servo |
Utility Functions in EnsembleBase Package | generate.partition generate.partitions load.object regression.extract.response rmse.error |
~~ Methods for Function 'validate' in Package 'EnsembleBase' ~~ | validate validate,Regression.Batch.FitObj-method validate,Regression.CV.Batch.FitObj-method validate-methods |