Package: randomForestVIP 0.1.3.9000
randomForestVIP: Tune Random Forests Based on Variable Importance and Plot Results
Functions for assessing variable relations and associations prior to modeling with a Random Forest algorithm (although these are relevant for any predictive model). Metrics such as partial correlations and variance inflation factors are tabulated as well as plotted for the user. A function is available for tuning the main Random Forest hyper-parameter based on model performance and variable importance metrics. This grid-search technique provides tables and plots showing the effect of the main hyper-parameter on each of the assessment metrics. It also returns each of the evaluated models to the user. The package also provides superior variable importance plots for individual models. All of the plots are developed so that the user has the ability to edit and improve further upon the plots. Derivations and methodology are described in Bladen (2022) <https://digitalcommons.usu.edu/etd/8587/>.
Authors:
randomForestVIP_0.1.3.9000.tar.gz
randomForestVIP_0.1.3.9000.zip(r-4.5)randomForestVIP_0.1.3.9000.zip(r-4.4)randomForestVIP_0.1.3.9000.zip(r-4.3)
randomForestVIP_0.1.3.9000.tgz(r-4.4-any)randomForestVIP_0.1.3.9000.tgz(r-4.3-any)
randomForestVIP_0.1.3.9000.tar.gz(r-4.5-noble)randomForestVIP_0.1.3.9000.tar.gz(r-4.4-noble)
randomForestVIP_0.1.3.9000.tgz(r-4.4-emscripten)randomForestVIP_0.1.3.9000.tgz(r-4.3-emscripten)
randomForestVIP.pdf |randomForestVIP.html✨
randomForestVIP/json (API)
# Install 'randomForestVIP' in R: |
install.packages('randomForestVIP', repos = c('https://kelvynbladen.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/kelvynbladen/randomforestvip/issues
Last updated 12 months agofrom:b9c5f647bc. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 26 2024 |
R-4.5-win | OK | Oct 26 2024 |
R-4.5-linux | OK | Oct 26 2024 |
R-4.4-win | OK | Oct 26 2024 |
R-4.4-mac | OK | Oct 26 2024 |
R-4.3-win | OK | Oct 26 2024 |
R-4.3-mac | OK | Oct 26 2024 |
Exports:caret_plotggvipmtry_comparemtry_pdp_comparepartial_corpdp_comparerobust_vifs
Dependencies:abindautocogsbackportsbase64encbootbroombslibcachemcallrcarcarDatacaretcheckmateclasscliclockcodetoolscolorspacecowplotcpp11crayondata.tableDerivdiagramdigestdiptestDistributionUtilsdoBydplyre1071evaluatefansifarverfastmapfontawesomeforeachFormulafsfuturefuture.applygbmgenericsggeasyggplot2globalsgluegowergridExtragtablehardhathexbinhighrhmshtmltoolshtmlwidgetsipredisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglatticelavalifecyclelistenvlme4lubridatemagrittrMASSMatrixMatrixModelsmclustmemoisemgcvmicrobenchmarkmimeminervaminqaModelMetricsmodelrmomentsmunsellnlmenloptrnnetnumDerivparallellypbkrtestpdppillarpkgconfigplyrprettyunitspROCprocessxprodlimprogressprogressrproxypspurrrquantregR6randomForestrappdirsRColorBrewerRcppRcppArmadilloRcppEigenrecipesreshape2rlangrmarkdownrpartsassscalesshapeSparseMSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetinytextrelliscopejstzdbutf8vctrsviridisLitewebshotwithrxfunyaml
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Housing Values in Suburbs of Boston | boston |
Plot Caret Grid Search Hyper-parameter Tuning Results | caret_plot |
Variable Importance GGPlot | ggvip |
Lichen data from the Current Vegetation Survey | lichen |
Mtry Tune via VIPs | mtry_compare |
Mtry Tune via PDPs | mtry_pdp_compare |
Partial Correlations | partial_cor |
Small Multiple PDPs and Importance Metrics | pdp_compare |
Non-linear Variance Inflation Factors | robust_vifs |