Package: ModTools 0.9.13
ModTools: Building Regression and Classification Models
Consistent user interface to the most common regression and classification algorithms, such as random forest, neural networks, C5 trees and support vector machines, complemented with a handful of auxiliary functions, such as variable importance and a tuning function for the parameters.
Authors:
ModTools_0.9.13.tar.gz
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ModTools.pdf |ModTools.html✨
ModTools/json (API)
NEWS
# Install 'ModTools' in R: |
install.packages('ModTools', repos = c('https://andrisignorell.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/andrisignorell/modtools/issues
Last updated 1 months agofrom:f543f2203d. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 30 2024 |
R-4.5-win | OK | Oct 30 2024 |
R-4.5-linux | OK | Oct 30 2024 |
R-4.4-win | OK | Oct 30 2024 |
R-4.4-mac | OK | Oct 30 2024 |
R-4.3-win | OK | Oct 30 2024 |
R-4.3-mac | OK | Oct 30 2024 |
Exports:BestCutBreuschPaganTestCoeffDiffCICPFitModLeafRatesLogitBoostNodeOverSamplePlotLiftPredictCIRefLevelResponseRobSummaryROCRulesSplitTrainTestTModCTuneUnderSampleVarImp
Dependencies:abindAERaskpassbackportsbitbit64bootbroomC50carcarDatacellrangerclassclicliprcolorspacecorpcorcowplotcpp11crayonCubistcurldata.tableDBIDEoptimRDerivDescToolsdoBydplyre1071ExactexpmfansifarverforcatsFormulagenericsggplot2gldgluegtablehavenhmshttrinumisobandjsonlitelabelinglatticelibcoinlifecyclelme4lmomlmtestmagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkmimeminqamitoolsmodelrmunsellmvtnormnaivebayesNeuralNetToolsnlmenloptrnnetnumDerivopensslpartykitpbkrtestpillarpkgconfigplyrprettyunitspROCprogressproxypsclpurrrquantregR6randomForestRColorBrewerRcppRcppArmadilloRcppEigenreadrreadxlrelaimporematchreshape2rlangrobustbaserootSolverpartrpart.plotrstudioapisandwichscalesSparseMstringistringrsurveysurvivalsystibbletidyrtidyselecttzdbutf8vctrsviridisLitevroomwithrzoo