Package: EnsemblePenReg 0.7
EnsemblePenReg: Extensible Classes and Methods for Penalized-Regression-Based Integration of Base Learners
Extending the base classes and methods of EnsembleBase package for Penalized-Regression-based (Ridge and Lasso) integration of base learners. Default implementation uses cross-validation error to choose the optimal lambda (shrinkage parameter) for the final predictor. The package takes advantage of the file method provided in EnsembleBase package for writing estimation objects to disk in order to circumvent RAM bottleneck. Special save and load methods are provided to allow estimation objects to be saved to permanent files on disk, and to be loaded again into temporary files in a later R session. Users and developers can extend the package by extending the generic methods and classes provided in EnsembleBase package as well as this package.
Authors:
EnsemblePenReg_0.7.tar.gz
EnsemblePenReg_0.7.zip(r-4.5)EnsemblePenReg_0.7.zip(r-4.4)EnsemblePenReg_0.7.zip(r-4.3)
EnsemblePenReg_0.7.tgz(r-4.4-any)EnsemblePenReg_0.7.tgz(r-4.3-any)
EnsemblePenReg_0.7.tar.gz(r-4.5-noble)EnsemblePenReg_0.7.tar.gz(r-4.4-noble)
EnsemblePenReg_0.7.tgz(r-4.4-emscripten)EnsemblePenReg_0.7.tgz(r-4.3-emscripten)
EnsemblePenReg.pdf |EnsemblePenReg.html✨
EnsemblePenReg/json (API)
# Install 'EnsemblePenReg' in R: |
install.packages('EnsemblePenReg', repos = c('https://asmahani.r-universe.dev', 'https://cloud.r-project.org')) |
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:8675fc9d99. Checks:OK: 5 NOTE: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Sep 04 2024 |
R-4.5-win | NOTE | Sep 04 2024 |
R-4.5-linux | NOTE | Sep 04 2024 |
R-4.4-win | OK | Sep 04 2024 |
R-4.4-mac | OK | Sep 04 2024 |
R-4.3-win | OK | Sep 04 2024 |
R-4.3-mac | OK | Sep 04 2024 |
Exports:epenregepenreg.baselearner.controlepenreg.integrator.controlepenreg.loadepenreg.saveRegression.Sweep.CV.Fit
Dependencies:bartMachinebartMachineJARsclassclicodetoolscpp11digestdoParalleldoRNGe1071EnsembleBaseforeachgbmglmnetglueigraphiteratorsitertoolskknnlatticelifecyclemagrittrMASSMatrixmissForestnnetpkgconfigproxyrandomForestRcppRcppEigenrJavarlangrngtoolsshapesurvivalvctrs
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Penalized-Regression-Based (PenReg) Integration of Base Learners for Ensemble Learning | epenreg |
Utility Functions for Configuring Regression Base Learners and Integrator in 'EnsemblePenReg' Package | epenreg.baselearner.control epenreg.integrator.control |
Custom Functions for Disk I/O in 'EnsemblePenReg' Package | epenreg.load epenreg.save |
Plot function for 'epenreg' model | plot.epenreg |
Predict method for class '"epenreg"' | predict.epenreg |
Class '"Regression.Integrator.PenReg.SelMin.Config"' | Regression.Integrator.PenReg.SelMin.Config-class |
Class '"Regression.Integrator.PenReg.SelMin.FitObj"' | Regression.Integrator.PenReg.SelMin.FitObj-class |
Function for cross-validation based sweep operation. | Regression.Sweep.CV.Fit |
Class '"Regression.Sweep.CV.FitObj"' | Regression.Sweep.CV.FitObj-class |
Class '"Regression.Sweep.PenReg.Config"' | Regression.Sweep.PenReg.Config-class |
Class '"Regression.Sweep.PenReg.FitObj"' | Regression.Sweep.PenReg.FitObj-class |