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:Mansour T.A. Sharabiani, Alireza S. Mahani

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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'))

Peer review:

Uses libs:
  • openjdk– OpenJDK Java runtime, using Hotspot JIT

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openjdk

1.00 score 1 stars 145 downloads 5 exports 37 dependencies

Last updated 8 years agofrom:cd071beb30. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 12 2024
R-4.5-winNOTEDec 12 2024
R-4.5-linuxNOTEDec 12 2024
R-4.4-winOKDec 12 2024
R-4.4-macOKDec 12 2024
R-4.3-winOKDec 12 2024
R-4.3-macOKDec 12 2024

Exports:ecv.loadecv.regressionecv.regression.baselearner.controlecv.regression.integrator.controlecv.save

Dependencies:bartMachinebartMachineJARsclassclicodetoolscpp11digestdoParalleldoRNGe1071EnsembleBaseforeachgbmglmnetglueigraphiteratorsitertoolskknnlatticelifecyclemagrittrMASSMatrixmissForestnnetpkgconfigproxyrandomForestRcppRcppEigenrJavarlangrngtoolsshapesurvivalvctrs