Package: metaEnsembleR 0.1.0

metaEnsembleR: Intuitive Package for Meta-Ensemble Learning (Classification, Regression) that is Fully-Automated

This package significantly lowers the barrier for the practitioners to apply heterogeneous ensemble learning techniques in an amateur fashion to their everyday predictive problems.

Authors:Ajay Arunachalam

metaEnsembleR_0.1.0.tar.gz
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metaEnsembleR.pdf |metaEnsembleR.html✨
metaEnsembleR/json (API)

# Install 'metaEnsembleR' in R:
install.packages('metaEnsembleR', repos = c('https://ajayarunachalam.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ajayarunachalam/metaensembler/issues

On CRAN:

Conda:

automationclassificationensemble-machine-learningensemble-methodsgeneralization-errorheterogenousmeta-learningpredictive-modelingregressionstacked-ensembles

3.70 score 165 downloads 2 exports 79 dependencies

Last updated 4 years agofrom:4379745243. Checks:1 OK, 8 WARNING. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 30 2025
R-4.5-winWARNINGMar 30 2025
R-4.5-macWARNINGMar 30 2025
R-4.5-linuxWARNINGMar 30 2025
R-4.4-winWARNINGMar 30 2025
R-4.4-macWARNINGMar 30 2025
R-4.4-linuxWARNINGMar 30 2025
R-4.3-winWARNINGMar 30 2025
R-4.3-macWARNINGMar 30 2025

Exports:ensembler.classifierensembler.regression

Dependencies:caretclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdplyre1071fansifarverforeachfuturefuture.applygbmgenericsggplot2globalsgluegowergridExtragtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6randomForestRColorBrewerRcpprecipesreshape2rlangrpartscalesshapesparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr

Intuitive Package for Meta-Ensemble Learning (Classification, Regression) that is Fully-Automated

Rendered frommetaEnsembleR.pdf.asisusingR.rsp::asison Mar 30 2025.

Last update: 2020-10-28
Started: 2020-10-28