Package: caret 7.0-1
caret: Classification and Regression Training
Misc functions for training and plotting classification and regression models.
Authors:
caret_7.0-1.tar.gz
caret_7.0-1.zip(r-4.7)caret_7.0-1.zip(r-4.6)caret_7.0-1.zip(r-4.5)
caret_7.0-1.tgz(r-4.6-x86_64)caret_7.0-1.tgz(r-4.6-arm64)caret_7.0-1.tgz(r-4.5-x86_64)caret_7.0-1.tgz(r-4.5-arm64)
caret_7.0-1.tar.gz(r-4.7-arm64)caret_7.0-1.tar.gz(r-4.7-x86_64)caret_7.0-1.tar.gz(r-4.6-arm64)caret_7.0-1.tar.gz(r-4.6-x86_64)
caret_7.0-1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
caret/json (API)
NEWS
| # Install 'caret' in R: |
| install.packages('caret', repos = c('https://topepo.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/topepo/caret/issues
- absorp - Fat, Water and Protein Content of Meat Samples
- bbbDescr - Blood Brain Barrier Data
- cars - Kelly Blue Book resale data for 2005 model year GM cars
- cox2Class - COX-2 Activity Data
- cox2Descr - COX-2 Activity Data
- cox2IC50 - COX-2 Activity Data
- dhfr - Dihydrofolate Reductase Inhibitors Data
- endpoints - Fat, Water and Protein Content of Meat Samples
- fattyAcids - Fatty acid composition of commercial oils
- GermanCredit - German Credit Data
- logBBB - Blood Brain Barrier Data
- mdrrClass - Multidrug Resistance Reversal (MDRR) Agent Data
- mdrrDescr - Multidrug Resistance Reversal (MDRR) Agent Data
- oilType - Fatty acid composition of commercial oils
- potteryClass - Pottery from Pre-Classical Sites in Italy
- Sacramento - Sacramento CA Home Prices
- scat - Morphometric Data on Scat
- scat_orig - Morphometric Data on Scat
- segmentationData - Cell Body Segmentation
Last updated from:c98cc1a3ba. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 293 | ||
| linux-devel-x86_64 | OK | 336 | ||
| source / vignettes | OK | 290 | ||
| linux-release-arm64 | OK | 335 | ||
| linux-release-x86_64 | OK | 359 | ||
| macos-release-arm64 | OK | 297 | ||
| macos-release-x86_64 | OK | 504 | ||
| macos-oldrel-arm64 | OK | 235 | ||
| macos-oldrel-x86_64 | OK | 383 | ||
| windows-devel | OK | 204 | ||
| windows-release | OK | 265 | ||
| windows-oldrel | OK | 306 | ||
| wasm-release | OK | 187 |
Exports:anovaScoresavNNetbagbagControlbagEarthbagEarthStatsbagFDAbestBoxCoxTranscalibrationcaretFuncscaretGAcaretSAcaretSBFcaretThemecforestStatscheckConditionalXcheckInstallcheckResamplesclass2indclassDistclustercompare_modelsconfusionMatrixconfusionMatrix.traincontr.dummycontr.ltfrcreateDataPartitioncreateFoldscreateModelcreateMultiFoldscreateResamplecreateTimeSlicesctreeBagdefaultSummarydotPlotdownSampledummyVarsexpandParametersexpoTransextractPredictionextractProbF_measfeaturePlotfilterVarImpfindCorrelationfindLinearCombosflatTablegafsgafs_initialgafs_lrSelectiongafs_raMutationgafs_rwSelectiongafs_spCrossovergafs_tourSelectiongafs_uCrossovergafs.defaultgafsControlgamFormulagamFuncsgamScoresgetModelInfogetSamplingInfogetTrainPerfggplot.gafsggplot.safsgroupKFoldhasTermsicrindex2vecipredStatsknn3knn3TrainknnregknnregTrainldaBagldaFuncsldaSBFlearning_curve_datliftlmFuncslmSBFLPH07_1LPH07_2lrFuncsMAEmaxDissimMeanSDminDissmnLogLossmodelCormodelLookupmultiClassSummarynbBagnbFuncsnbSBFnearZeroVarnegPredValuennetBagnullModelnzvoneSEoutcome_conversionpanel.calibrationpanel.liftpanel.lift2panel.needlepcaNNetpickSizeBestpickSizeTolerancepickVarsplot.gafsplot.rfeplot.safsplot.trainplotClassProbsplotObsVsPredplsBagplsdaposPredValuepostResampleprecisionpredict.bagEarthpredict.gafspredict.trainpredictionFunctionpredictorspreProcessprint.trainprobFunctionprogressprSummaryR2recallresampleHistresamplesresampleSummaryresampleWrapperrferfeControlrfeIterrfFuncsrfGArfSArfSBFrfStatsRMSEsafssafs_initialsafs_perturbsafs_probsafsControlsbfsbfControlsbfItersensitivitySLC14_1SLC14_2sortImpspatialSignspecificitysplsdasumDisssummary.bagEarthsvmBagthresholdertolerancetraintrainControltreebagFuncstreebagGAtreebagSAtreebagSBFtwoClassSimtwoClassSummaryupSamplevar_seqvarImpwell_numbered
Dependencies:classcliclockcodetoolscpp11data.tablediagramdigestdplyre1071farverforeachfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixModelMetricsnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcpprecipesreshape2rlangrpartS7scalesshapesparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Confusion matrix as a table | as.matrix.confusionMatrix as.table.confusionMatrix |
| Neural Networks Using Model Averaging | avNNet avNNet.default avNNet.formula predict.avNNet print.avNNet |
| A General Framework For Bagging | bag bag.default bagControl ctreeBag ldaBag nbBag nnetBag plsBag predict.bag print.bag print.summary.bag summary.bag svmBag |
| Bagged Earth | bagEarth bagEarth.default bagEarth.formula print.bagEarth |
| Bagged FDA | bagFDA bagFDA.default bagFDA.formula print.bagFDA |
| Blood Brain Barrier Data | bbbDescr BloodBrain logBBB |
| Box-Cox and Exponential Transformations | BoxCoxTrans BoxCoxTrans.default expoTrans expoTrans.default predict.BoxCoxTrans predict.expoTrans print.BoxCoxTrans |
| Probability Calibration Plot | calibration calibration.default calibration.formula ggplot.calibration panel.calibration print.calibration xyplot.calibration |
| Selection By Filtering (SBF) Helper Functions | anovaScores caretSBF gamScores ldaSBF lmSBF nbSBF rfSBF treebagSBF |
| Kelly Blue Book resale data for 2005 model year GM cars | cars |
| Compute and predict the distances to class centroids | classDist classDist.default predict.classDist |
| Create a confusion matrix | confusionMatrix confusionMatrix.default confusionMatrix.matrix confusionMatrix.table |
| Estimate a Resampled Confusion Matrix | confusionMatrix.rfe confusionMatrix.sbf confusionMatrix.train |
| COX-2 Activity Data | cox2 cox2Class cox2Descr cox2IC50 |
| Data Splitting functions | createDataPartition createFolds createMultiFolds createResample createTimeSlices groupKFold |
| Calculates performance across resamples | defaultSummary getTrainPerf MAE mnLogLoss multiClassSummary postResample prSummary R2 RMSE twoClassSummary |
| Lattice functions for plotting resampling results of recursive feature selection | densityplot.rfe histogram.rfe stripplot.rfe xyplot.rfe |
| Dihydrofolate Reductase Inhibitors Data | dhfr |
| Inferential Assessments About Model Performance | compare_models diff.resamples summary.diff.resamples |
| Create a dotplot of variable importance values | dotPlot |
| Lattice Functions for Visualizing Resampling Differences | bwplot.diff.resamples densityplot.diff.resamples dotplot.diff.resamples levelplot.diff.resamples |
| Down- and Up-Sampling Imbalanced Data | downSample upSample |
| Create A Full Set of Dummy Variables | class2ind contr.dummy contr.ltfr dummyVars dummyVars.default predict.dummyVars print.dummyVars |
| Extract predictions and class probabilities from train objects | extractPrediction extractProb predict.list predict.train |
| Wrapper for Lattice Plotting of Predictor Variables | featurePlot |
| Calculation of filter-based variable importance | filterVarImp |
| Determine highly correlated variables | findCorrelation |
| Determine linear combinations in a matrix | findLinearCombos |
| Format 'bagEarth' objects | format.bagEarth |
| Ancillary genetic algorithm functions | caretGA gafs_initial gafs_lrSelection gafs_nlrSelection gafs_raMutation gafs_rwSelection gafs_spCrossover gafs_tourSelection gafs_uCrossover rfGA treebagGA |
| Genetic algorithm feature selection | gafs gafs.default gafs.recipe |
| Control parameters for GA and SA feature selection | gafsControl safsControl |
| German Credit Data | GermanCredit |
| Get sampling info from a train model | getSamplingInfo |
| Plot RFE Performance Profiles | ggplot.rfe plot.rfe |
| Plot Method for the train Class | ggplot.train plot.train |
| Lattice functions for plotting resampling results | densityplot.train histogram.train stripplot.train xyplot.train |
| Independent Component Regression | icr icr.default icr.formula predict.icr |
| Convert indicies to a binary vector | index2vec |
| k-Nearest Neighbour Classification | knn3 knn3.data.frame knn3.formula knn3.matrix knn3Train print.knn3 |
| k-Nearest Neighbour Regression | knnreg knnreg.data.frame knnreg.default knnreg.formula knnreg.matrix knnregTrain print.knnreg |
| Create Data to Plot a Learning Curve | learning_curve_dat |
| Lift Plot | ggplot.lift lift lift.default lift.formula print.lift xyplot.lift |
| Maximum Dissimilarity Sampling | maxDissim minDiss sumDiss |
| Multidrug Resistance Reversal (MDRR) Agent Data | mdrr mdrrClass mdrrDescr |
| Tools for Models Available in 'train' | checkInstall getModelInfo modelLookup |
| Identification of near zero variance predictors | checkConditionalX checkResamples nearZeroVar nzv |
| Calculate sensitivity, specificity and predictive values | negPredValue negPredValue.default negPredValue.matrix negPredValue.table posPredValue posPredValue.default posPredValue.matrix posPredValue.table sensitivity sensitivity.default sensitivity.matrix sensitivity.table specificity specificity.default specificity.matrix specificity.table |
| Fit a simple, non-informative model | nullModel nullModel.default predict.nullModel |
| Fatty acid composition of commercial oils | fattyAcids oil oilType |
| Selecting tuning Parameters | best oneSE tolerance |
| Lattice Panel Functions for Lift Plots | panel.lift panel.lift2 |
| Needle Plot Lattice Panel | panel.needle |
| Neural Networks with a Principal Component Step | pcaNNet pcaNNet.default pcaNNet.formula predict.pcaNNet print.pcaNNet |
| Backwards Feature Selection Helper Functions | caretFuncs gamFuncs ldaFuncs lmFuncs lrFuncs nbFuncs pickSizeBest pickSizeTolerance pickVars rfFuncs treebagFuncs |
| Plot Method for the gafs and safs Classes | ggplot.gafs ggplot.safs plot.gafs plot.safs |
| Plotting variable importance measures | ggplot.varImp.train plot.varImp.train |
| Plot Predicted Probabilities in Classification Models | plotClassProbs |
| Plot Observed versus Predicted Results in Regression and Classification Models | plotObsVsPred |
| Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis | plsda plsda.default predict.plsda predict.splsda splsda splsda.default |
| Pottery from Pre-Classical Sites in Italy | pottery potteryClass |
| Principal Components Analysis of Resampling Results | cluster cluster.resamples plot.prcomp.resamples prcomp.resamples |
| Predicted values based on bagged Earth and FDA models | predict.bagEarth predict.bagFDA |
| Predict new samples | predict.gafs predict.safs |
| Predictions from k-Nearest Neighbors | predict.knn3 |
| Predictions from k-Nearest Neighbors Regression Model | predict.knnreg |
| List predictors used in the model | predictors predictors.default predictors.formula predictors.list predictors.rfe predictors.sbf predictors.terms predictors.train |
| Pre-Processing of Predictors | predict.preProcess preProcess preProcess.default |
| Print method for confusionMatrix | print.confusionMatrix |
| Print Method for the train Class | print.train |
| Calculate recall, precision and F values | F_meas F_meas.default F_meas.table precision precision.default precision.matrix precision.table recall recall.default recall.table |
| Plot the resampling distribution of the model statistics | resampleHist |
| Collation and Visualization of Resampling Results | as.data.frame.resamples as.matrix.resamples modelCor print.resamples resamples resamples.default sort.resamples summary.resamples |
| Summary of resampled performance estimates | resampleSummary |
| Backwards Feature Selection | predict.rfe rfe rfe.default rfe.formula rfe.recipe rfeIter update.rfe |
| Controlling the Feature Selection Algorithms | rfeControl |
| Sacramento CA Home Prices | Sacramento |
| Simulated annealing feature selection | safs safs.default safs.recipe |
| Ancillary simulated annealing functions | caretSA rfSA safs_initial safs_perturb safs_prob treebagSA |
| Selection By Filtering (SBF) | predict.sbf sbf sbf.default sbf.formula sbf.recipe |
| Control Object for Selection By Filtering (SBF) | sbfControl |
| Morphometric Data on Scat | scat scat_orig |
| Cell Body Segmentation | segmentationData |
| Simulation Functions | LPH07_1 LPH07_2 SLC14_1 SLC14_2 twoClassSim |
| Compute the multivariate spatial sign | spatialSign spatialSign.data.frame spatialSign.default spatialSign.matrix |
| Summarize a bagged earth or FDA fit | summary.bagEarth summary.bagFDA |
| Fat, Water and Protein Content of Meat Samples | absorp endpoints tecator |
| Generate Data to Choose a Probability Threshold | thresholder |
| Fit Predictive Models over Different Tuning Parameters | train train.default train.formula train.recipe |
| A List of Available Models in train | models train_model_list |
| Control parameters for train | trainControl |
| Update or Re-fit a SA or GA Model | update.gafs update.safs |
| Update or Re-fit a Model | update.train |
| Sequences of Variables for Tuning | var_seq |
| Calculation of variable importance for regression and classification models | varImp varImp.avNNet varImp.bagEarth varImp.bagFDA varImp.C5.0 varImp.classbagg varImp.cubist varImp.dsa varImp.earth varImp.fda varImp.Gam varImp.gam varImp.gbm varImp.glm varImp.glmnet varImp.JRip varImp.lm varImp.multinom varImp.mvr varImp.nnet varImp.pamrtrained varImp.PART varImp.plsda varImp.RandomForest varImp.randomForest varImp.regbagg varImp.rfe varImp.rpart varImp.RRF varImp.train |
| Variable importances for GAs and SAs | varImp.gafs varImp.safs |
| Lattice Functions for Visualizing Resampling Results | bwplot.resamples densityplot.resamples dotplot.resamples ggplot.resamples parallelplot.resamples splom.resamples xyplot.resamples |
