caret v6.0-58
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by Max Kuhn
Classification and Regression Training
Misc functions for training and plotting classification and
regression models.
Functions in caret
| Name | Description | |
| findCorrelation | Determine highly correlated variables | |
| bagEarth | Bagged Earth | |
| lattice.rfe | Lattice functions for plotting resampling results of recursive feature selection | |
| nullModel | Fit a simple, non-informative model | |
| as.table.confusionMatrix | Save Confusion Table Results | |
| pottery | Pottery from Pre-Classical Sites in Italy | |
| plot.rfe | Plot RFE Performance Profiles | |
| sbfControl | Control Object for Selection By Filtering (SBF) | |
| oneSE | Selecting tuning Parameters | |
| spatialSign | Compute the multivariate spatial sign | |
| plsda | Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis | |
| BloodBrain | Blood Brain Barrier Data | |
| confusionMatrix | Create a confusion matrix | |
| BoxCoxTrans.default | Box-Cox and Exponential Transformations | |
| dummyVars | Create A Full Set of Dummy Variables | |
| avNNet.default | Neural Networks Using Model Averaging | |
| getSamplingInfo | Get sampling info from a train model | |
| lift | Lift Plot | |
| downSample | Down- and Up-Sampling Imbalanced Data | |
| GermanCredit | German Credit Data | |
| bag.default | A General Framework For Bagging | |
| panel.needle | Needle Plot Lattice Panel | |
| predictors | List predictors used in the model | |
| dhfr | Dihydrofolate Reductase Inhibitors Data | |
| classDist | Compute and predict the distances to class centroids | |
| confusionMatrix.train | Estimate a Resampled Confusion Matrix | |
| gafs.default | Genetic algorithm feature selection | |
| plot.gafs | Plot Method for the gafs and safs Classes | |
| caretFuncs | Backwards Feature Selection Helper Functions | |
| index2vec | Convert indicies to a binary vector | |
| resampleHist | Plot the resampling distribution of the model statistics | |
| icr.formula | Independent Component Regression | |
| diff.resamples | Inferential Assessments About Model Performance | |
| knnreg | k-Nearest Neighbour Regression | |
| predict.train | Extract predictions and class probabilities from train objects | |
| oil | Fatty acid composition of commercial oils | |
| xyplot.resamples | Lattice Functions for Visualizing Resampling Results | |
| calibration | Probability Calibration Plot | |
| plotObsVsPred | Plot Observed versus Predicted Results in Regression and Classification Models | |
| postResample | Calculates performance across resamples | |
| plot.varImp.train | Plotting variable importance measures | |
| maxDissim | Maximum Dissimilarity Sampling | |
| featurePlot | Wrapper for Lattice Plotting of Predictor Variables | |
| knn3 | k-Nearest Neighbour Classification | |
| resampleSummary | Summary of resampled performance estimates | |
| histogram.train | Lattice functions for plotting resampling results | |
| predict.bagEarth | Predicted values based on bagged Earth and FDA models | |
| plot.train | Plot Method for the train Class | |
| dotPlot | Create a dotplot of variable importance values | |
| print.confusionMatrix | Print method for confusionMatrix | |
| prcomp.resamples | Principal Components Analysis of Resampling Results | |
| format.bagEarth | Format 'bagEarth' objects | |
| update.train | Update or Re-fit a Model | |
| predict.gafs | Predict new samples | |
| safsControl | Control parameters for GA and SA feature selection | |
| panel.lift2 | Lattice Panel Functions for Lift Plots | |
| safs.default | Simulated annealing feature selection | |
| tecator | Fat, Water and Protein Content of Meat Samples | |
| caretSBF | Selection By Filtering (SBF) Helper Functions | |
| findLinearCombos | Determine linear combinations in a matrix | |
| cars | Kelly Blue Book resale data for 2005 model year GM cars | |
| segmentationData | Cell Body Segmentation | |
| summary.bagEarth | Summarize a bagged earth or FDA fit | |
| sbf | Selection By Filtering (SBF) | |
| predict.knn3 | Predictions from k-Nearest Neighbors | |
| varImp.gafs | Variable importances for GAs and SAs | |
| twoClassSim | Simulation Functions | |
| print.train | Print Method for the train Class | |
| var_seq | Sequences of Variables for Tuning | |
| rfe | Backwards Feature Selection | |
| pcaNNet.default | Neural Networks with a Principal Component Step | |
| safs_initial | Ancillary simulated annealing functions | |
| nearZeroVar | Identification of near zero variance predictors | |
| sensitivity | Calculate sensitivity, specificity and predictive values | |
| bagFDA | Bagged FDA | |
| dotplot.diff.resamples | Lattice Functions for Visualizing Resampling Differences | |
| modelLookup | Tools for Models Available in train | |
| mdrr | Multidrug Resistance Reversal (MDRR) Agent Data | |
| train_model_list | A List of Available Models in train | |
| preProcess | Pre-Processing of Predictors | |
| createDataPartition | Data Splitting functions | |
| plotClassProbs | Plot Predicted Probabilities in Classification Models | |
| rfeControl | Controlling the Feature Selection Algorithms | |
| update.safs | Update or Re-fit a SA or GA Model | |
| trainControl | Control parameters for train | |
| filterVarImp | Calculation of filter-based variable importance | |
| varImp | Calculation of variable importance for regression and classification models | |
| caret-internal | Internal Functions | |
| resamples | Collation and Visualization of Resampling Results | |
| predict.knnreg | Predictions from k-Nearest Neighbors Regression Model | |
| gafs_initial | Ancillary genetic algorithm functions | |
| cox2 | COX-2 Activity Data | |
| train | Fit Predictive Models over Different Tuning Parameters | |
| No Results! | ||
Last month downloads
Details
| Date | 2015-10-20 |
| URL | https://github.com/topepo/caret/ |
| BugReports | https://github.com/topepo/caret/issues |
| License | GPL (>= 2) |
| NeedsCompilation | yes |
| Packaged | 2015-10-21 14:20:28 UTC; kuhna03 |
| Repository | CRAN |
| Date/Publication | 2015-10-22 08:24:13 |
| depends | base (>= 2.10) , ggplot2 , lattice (>= 0.20) , R (>= 2.10) |
| suggests | BradleyTerry2 , Cubist , e1071 , earth (>= 2.2-3) , ellipse , fastICA , gam , ipred , kernlab , klaR , MASS , mda , mgcv , mlbench , nnet , pamr , party (>= 0.9-99992) , pls , pROC (>= 1.8) , proxy , randomForest , RANN , rPython , spls , subselect , superpc , testthat (>= 0.9.1) |
| imports | car , foreach , grDevices , methods , nlme , plyr , reshape2 , stats , stats4 , utils |
| Contributors | the Core team, Brenton Kenkel, Max Contributions from Jed Wing, Steve Weston, Andre Williams, Chris Keefer, Allan Engelhardt, Tony Cooper, Zachary Mayer, Michael Benesty, Reynald Lescarbeau, Andrew Ziem, Luca Scrucca, Yuan Tang, Can Candan |
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