Package: caretEnsemble 4.0.1

caretEnsemble: Ensembles of Caret Models

Functions for creating ensembles of caret models: caretList() and caretStack(). caretList() is a convenience function for fitting multiple caret::train() models to the same dataset. caretStack() will make linear or non-linear combinations of these models, using a caret::train() model as a meta-model.

Authors:Zachary A. Deane-Mayer [aut, cre, cph], Jared E. Knowles [ctb], Antón López [ctb]

caretEnsemble_4.0.1.tar.gz
caretEnsemble_4.0.1.zip(r-4.5)caretEnsemble_4.0.1.zip(r-4.4)caretEnsemble_4.0.1.zip(r-4.3)
caretEnsemble_4.0.1.tgz(r-4.4-any)caretEnsemble_4.0.1.tgz(r-4.3-any)
caretEnsemble_4.0.1.tar.gz(r-4.5-noble)caretEnsemble_4.0.1.tar.gz(r-4.4-noble)
caretEnsemble_4.0.1.tgz(r-4.4-emscripten)caretEnsemble_4.0.1.tgz(r-4.3-emscripten)
caretEnsemble.pdf |caretEnsemble.html✨
caretEnsemble/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/zachmayer/caretensemble/issues

Datasets:

    On CRAN:

    11.52 score 226 stars 780 scripts 2.9k downloads 8 mentions 13 exports 77 dependencies

    Last updated 2 months agofrom:6722ffca95. Checks:OK: 7. Indexed: yes.

    TargetResultDate
    Doc / VignettesOKNov 14 2024
    R-4.5-winOKNov 14 2024
    R-4.5-linuxOKNov 14 2024
    R-4.4-winOKNov 14 2024
    R-4.4-macOKNov 14 2024
    R-4.3-winOKNov 14 2024
    R-4.3-macOKNov 14 2024

    Exports:as.caretListcaretEnsemblecaretListcaretModelSpeccaretStackdefaultControldefaultMetricextractMetricgreedyMSEgreedyMSE_caretpermutationImportancetuneCheckwtd.sd

    Dependencies:caretclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdplyre1071fansifarverforeachfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypatchworkpbapplypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcpprecipesreshape2rlangrpartscalesshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr

    A Brief Introduction to caretEnsemble

    Zach Deane-Mayer

    Rendered fromcaretEnsemble-intro.Rmdusingknitr::rmarkdownon Nov 14 2024.

    Last update: 2024-08-13
    Started: 2014-11-22

    Version 4.0 New Features

    Zach Deane-Mayer

    Rendered fromVersion-4.0-New-Features.Rmdusingknitr::rmarkdownon Nov 14 2024.

    Last update: 2024-08-13
    Started: 2024-08-13

    Readme and manuals

    Help Manual

    Help pageTopics
    Index a caretList[.caretList
    Convert object to caretList objectas.caretList
    Convert object to caretList object - For Future Useas.caretList.default
    Convert list to caretListas.caretList.list
    Convenience function for more in-depth diagnostic plots of caretStack objectsautoplot.caretStack
    S3 definition for concatenating caretListc.caretList
    S3 definition for concatenating train objectsc.train
    Combine several predictive models via weightscaretEnsemble-package caretEnsemble
    Create a list of several train models from the caret packagecaretList
    Generate a specification for fitting a caret modelcaretModelSpec
    Combine several predictive models via stackingcaretStack
    Construct a default train control for use with caretListdefaultControl
    Construct a default metricdefaultMetric
    Comparison dotplot for a caretStack objectdotplot.caretStack
    Generic function to extract accuracy metrics from various model objectsextractMetric
    Extract accuracy metrics from a 'caretList' objectextractMetric.caretList
    Extract accuracy metrics from a 'caretStack' objectextractMetric.caretStack
    Extract accuracy metrics from a 'train' modelextractMetric.train
    Greedy optimization for MSEgreedyMSE
    caret interface for greedyMSEgreedyMSE_caret
    Permutation ImportancepermutationImportance
    Plot a caretList objectplot.caretList
    Plot a caretStack objectplot.caretStack
    Create a matrix of predictions for each of the models in a caretListpredict.caretList
    Make predictions from a caretStackpredict.caretStack
    Predict method for greedyMSEpredict.greedyMSE
    Print a caretStack objectprint.caretStack
    Print method for greedyMSEprint.greedyMSE
    Print a summary.caretList objectprint.summary.caretList
    Print a summary.caretStack objectprint.summary.caretStack
    Summarize a caretListsummary.caretList
    Summarize a caretStack objectsummary.caretStack
    Check that the tuning parameters list supplied by the user is validtuneCheck
    Variable importance for caretStackvarImp.caretStack
    variable importance for a greedyMSE modelvarImp.greedyMSE
    Calculate a weighted standard deviationwtd.sd