Package: EnsembleCV 0.8
EnsembleCV: Extensible Package for Cross-Validation-Based Integration of Base Learners
Extends the base classes and methods of EnsembleBase package for cross-validation-based integration of base learners. Default implementation calculates average of repeated CV errors, and selects the base learner / configuration with minimum average error. 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. The package can be extended, e.g. by adding variants of the current implementation.
Authors:
EnsembleCV_0.8.tar.gz
EnsembleCV_0.8.zip(r-4.5)EnsembleCV_0.8.zip(r-4.4)EnsembleCV_0.8.zip(r-4.3)
EnsembleCV_0.8.tgz(r-4.4-any)EnsembleCV_0.8.tgz(r-4.3-any)
EnsembleCV_0.8.tar.gz(r-4.5-noble)EnsembleCV_0.8.tar.gz(r-4.4-noble)
EnsembleCV_0.8.tgz(r-4.4-emscripten)EnsembleCV_0.8.tgz(r-4.3-emscripten)
EnsembleCV.pdf |EnsembleCV.html✨
EnsembleCV/json (API)
# Install 'EnsembleCV' in R: |
install.packages('EnsembleCV', 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:cd071beb30. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Aug 14 2024 |
R-4.5-win | OK | Aug 14 2024 |
R-4.5-linux | OK | Aug 14 2024 |
R-4.4-win | OK | Aug 14 2024 |
R-4.4-mac | OK | Aug 14 2024 |
R-4.3-win | OK | Aug 14 2024 |
R-4.3-mac | OK | Aug 14 2024 |
Exports:ecv.loadecv.regressionecv.regression.baselearner.controlecv.regression.integrator.controlecv.save
Dependencies:bartMachinebartMachineJARsclassclicodetoolscpp11digestdoParalleldoRNGe1071EnsembleBaseforeachgbmglmnetglueigraphiteratorsitertoolskknnlatticelifecyclemagrittrMASSMatrixmissForestnnetpkgconfigproxyrandomForestRcppRcppEigenrJavarlangrngtoolsshapesurvivalvctrs
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Cross-Validation-Based Integration of Regression Base Learners for Ensemble Learning | ecv.regression |
Utility Functions for Configuring Regression Base Learners and Integrator in 'EnsembleCV' Package | ecv.regression.baselearner.control ecv.regression.integrator.control |
Custom Functions for Disk I/O in 'EnsembleCV' Package | ecv.load ecv.save |
S3 Methods for class '"ecv.regression"' | plot.ecv.regression predict.ecv.regression |
Class '"Regression.Select.MinAvgErr.Config"' | Regression.Select.MinAvgErr.Config-class |
Class '"Regression.Select.MinAvgErr.FitObj"' | Regression.Select.MinAvgErr.FitObj-class |