Package: manymodelr 0.3.8.9000

manymodelr: Build and Tune Several Models

Frequently one needs a convenient way to build and tune several models in one go.The goal is to provide a number of machine learning convenience functions. It provides the ability to build, tune and obtain predictions of several models in one function. The models are built using functions from 'caret' with easier to read syntax. Kuhn(2014) <arxiv:1405.6974>.

Authors:Nelson Gonzabato [aut, cre]

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Bug tracker:https://github.com/nelson-gon/manymodelr/issues

On CRAN:

analysis-of-varianceanovacorrelationcorrelation-coefficientgeneralized-linear-modelsgradient-boosting-decision-treesknn-classificationlinear-modelslinear-regressionmachine-learningmissing-valuesmodelsr-programmingrandom-forest-algorithmregression-models

23 exports 2 stars 0.94 score 81 dependencies 50 scripts 322 downloads

Last updated 3 years agofrom:29c73d4c55. Checks:OK: 7. Indexed: yes.

Exports:add_model_predictionsadd_model_residualsagg_by_groupdrop_non_numericextract_model_infofit_modelfit_modelsget_data_Statsget_exponentget_modeget_statsget_thisget_var_corrget_var_corr_multi_model_1multi_model_2na_replacena_replace_groupedplot_corrreport_modelrowdiffselect_colselect_percentile

Dependencies:bootcaretclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdplyre1071fansifarverforeachfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlme4lubridatemagrittrMASSMatrixMetricsmgcvminqaModelMetricsmunsellnlmenloptrnnetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcppRcppEigenrecipesreshape2rlangrpartscalesshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr