Man pages for caret
Classification and Regression Training
| as.matrix.confusionMatrix | Confusion matrix as a table |
| avNNet | Neural Networks Using Model Averaging |
| bag | A General Framework For Bagging |
| bagEarth | Bagged Earth |
| bagFDA | Bagged FDA |
| BloodBrain | Blood Brain Barrier Data |
| BoxCoxTrans | Box-Cox and Exponential Transformations |
| calibration | Probability Calibration Plot |
| caretFuncs | Backwards Feature Selection Helper Functions |
| caret-internal | Internal Functions |
| caretSBF | Selection By Filtering (SBF) Helper Functions |
| cars | Kelly Blue Book resale data for 2005 model year GM cars |
| classDist | Compute and predict the distances to class centroids |
| confusionMatrix | Create a confusion matrix |
| confusionMatrix.train | Estimate a Resampled Confusion Matrix |
| cox2 | COX-2 Activity Data |
| createDataPartition | Data Splitting functions |
| densityplot.rfe | Lattice functions for plotting resampling results of... |
| dhfr | Dihydrofolate Reductase Inhibitors Data |
| diff.resamples | Inferential Assessments About Model Performance |
| dotPlot | Create a dotplot of variable importance values |
| dotplot.diff.resamples | Lattice Functions for Visualizing Resampling Differences |
| downSample | Down- and Up-Sampling Imbalanced Data |
| dummyVars | Create A Full Set of Dummy Variables |
| featurePlot | Wrapper for Lattice Plotting of Predictor Variables |
| filterVarImp | Calculation of filter-based variable importance |
| findCorrelation | Determine highly correlated variables |
| findLinearCombos | Determine linear combinations in a matrix |
| format.bagEarth | Format 'bagEarth' objects |
| gafs.default | Genetic algorithm feature selection |
| gafs_initial | Ancillary genetic algorithm functions |
| GermanCredit | German Credit Data |
| getSamplingInfo | Get sampling info from a train model |
| histogram.train | Lattice functions for plotting resampling results |
| icr.formula | Independent Component Regression |
| index2vec | Convert indicies to a binary vector |
| knn3 | k-Nearest Neighbour Classification |
| knnreg | k-Nearest Neighbour Regression |
| learning_curve_dat | Create Data to Plot a Learning Curve |
| lift | Lift Plot |
| maxDissim | Maximum Dissimilarity Sampling |
| mdrr | Multidrug Resistance Reversal (MDRR) Agent Data |
| modelLookup | Tools for Models Available in 'train' |
| models | A List of Available Models in train |
| nearZeroVar | Identification of near zero variance predictors |
| nullModel | Fit a simple, non-informative model |
| oil | Fatty acid composition of commercial oils |
| oneSE | Selecting tuning Parameters |
| panel.lift2 | Lattice Panel Functions for Lift Plots |
| panel.needle | Needle Plot Lattice Panel |
| pcaNNet | Neural Networks with a Principal Component Step |
| plotClassProbs | Plot Predicted Probabilities in Classification Models |
| plot.gafs | Plot Method for the gafs and safs Classes |
| plotObsVsPred | Plot Observed versus Predicted Results in Regression and... |
| plot.rfe | Plot RFE Performance Profiles |
| plot.train | Plot Method for the train Class |
| plot.varImp.train | Plotting variable importance measures |
| plsda | Partial Least Squares and Sparse Partial Least Squares... |
| postResample | Calculates performance across resamples |
| pottery | Pottery from Pre-Classical Sites in Italy |
| prcomp.resamples | Principal Components Analysis of Resampling Results |
| predict.bagEarth | Predicted values based on bagged Earth and FDA models |
| predict.gafs | Predict new samples |
| predict.knn3 | Predictions from k-Nearest Neighbors |
| predict.knnreg | Predictions from k-Nearest Neighbors Regression Model |
| predictors | List predictors used in the model |
| predict.train | Extract predictions and class probabilities from train... |
| preProcess | Pre-Processing of Predictors |
| print.confusionMatrix | Print method for confusionMatrix |
| print.train | Print Method for the train Class |
| recall | Calculate recall, precision and F values |
| resampleHist | Plot the resampling distribution of the model statistics |
| resamples | Collation and Visualization of Resampling Results |
| resampleSummary | Summary of resampled performance estimates |
| rfe | Backwards Feature Selection |
| rfeControl | Controlling the Feature Selection Algorithms |
| Sacramento | Sacramento CA Home Prices |
| safs | Simulated annealing feature selection |
| safsControl | Control parameters for GA and SA feature selection |
| safs_initial | Ancillary simulated annealing functions |
| sbf | Selection By Filtering (SBF) |
| sbfControl | Control Object for Selection By Filtering (SBF) |
| scat | Morphometric Data on Scat |
| segmentationData | Cell Body Segmentation |
| sensitivity | Calculate sensitivity, specificity and predictive values |
| spatialSign | Compute the multivariate spatial sign |
| summary.bagEarth | Summarize a bagged earth or FDA fit |
| tecator | Fat, Water and Protein Content of Meat Samples |
| thresholder | Generate Data to Choose a Probability Threshold |
| train | Fit Predictive Models over Different Tuning Parameters |
| trainControl | Control parameters for train |
| twoClassSim | Simulation Functions |
| update.safs | Update or Re-fit a SA or GA Model |
| update.train | Update or Re-fit a Model |
| varImp | Calculation of variable importance for regression and... |
| varImp.gafs | Variable importances for GAs and SAs |
| var_seq | Sequences of Variables for Tuning |
| xyplot.resamples | Lattice Functions for Visualizing Resampling Results |
