caret v6.0-57
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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 | |
| bagFDA | Bagged FDA | |
| featurePlot | Wrapper for Lattice Plotting of Predictor Variables | |
| caret-internal | Internal Functions | |
| cars | Kelly Blue Book resale data for 2005 model year GM cars | |
| diff.resamples | Inferential Assessments About Model Performance | |
| dhfr | Dihydrofolate Reductase Inhibitors Data | |
| filterVarImp | Calculation of filter-based variable importance | |
| predict.train | Extract predictions and class probabilities from train objects | |
| twoClassSim | Simulation Functions | |
| calibration | Probability Calibration Plot | |
| gafs_initial | Ancillary genetic algorithm functions | |
| modelLookup | Tools for Models Available in train | |
| dummyVars | Create A Full Set of Dummy Variables | |
| print.train | Print Method for the train Class | |
| update.train | Update or Re-fit a Model | |
| mdrr | Multidrug Resistance Reversal (MDRR) Agent Data | |
| getSamplingInfo | Get sampling info from a train model | |
| knnreg | k-Nearest Neighbour Regression | |
| dotplot.diff.resamples | Lattice Functions for Visualizing Resampling Differences | |
| BloodBrain | Blood Brain Barrier Data | |
| bag.default | A General Framework For Bagging | |
| BoxCoxTrans.default | Box-Cox and Exponential Transformations | |
| print.confusionMatrix | Print method for confusionMatrix | |
| createDataPartition | Data Splitting functions | |
| resampleSummary | Summary of resampled performance estimates | |
| trainControl | Control parameters for train | |
| rfeControl | Controlling the Feature Selection Algorithms | |
| as.table.confusionMatrix | Save Confusion Table Results | |
| preProcess | Pre-Processing of Predictors | |
| prcomp.resamples | Principal Components Analysis of Resampling Results | |
| avNNet.default | Neural Networks Using Model Averaging | |
| panel.needle | Needle Plot Lattice Panel | |
| lift | Lift Plot | |
| icr.formula | Independent Component Regression | |
| predictors | List predictors used in the model | |
| var_seq | Sequences of Variables for Tuning | |
| confusionMatrix.train | Estimate a Resampled Confusion Matrix | |
| classDist | Compute and predict the distances to class centroids | |
| caretFuncs | Backwards Feature Selection Helper Functions | |
| index2vec | Convert indicies to a binary vector | |
| plotClassProbs | Plot Predicted Probabilities in Classification Models | |
| sbfControl | Control Object for Selection By Filtering (SBF) | |
| pottery | Pottery from Pre-Classical Sites in Italy | |
| cox2 | COX-2 Activity Data | |
| predict.knn3 | Predictions from k-Nearest Neighbors | |
| resamples | Collation and Visualization of Resampling Results | |
| dotPlot | Create a dotplot of variable importance values | |
| safs.default | Simulated annealing feature selection | |
| sbf | Selection By Filtering (SBF) | |
| plot.rfe | Plot RFE Performance Profiles | |
| predict.gafs | Predict new samples | |
| xyplot.resamples | Lattice Functions for Visualizing Resampling Results | |
| lattice.rfe | Lattice functions for plotting resampling results of recursive feature selection | |
| nearZeroVar | Identification of near zero variance predictors | |
| tecator | Fat, Water and Protein Content of Meat Samples | |
| summary.bagEarth | Summarize a bagged earth or FDA fit | |
| nullModel | Fit a simple, non-informative model | |
| histogram.train | Lattice functions for plotting resampling results | |
| plsda | Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis | |
| knn3 | k-Nearest Neighbour Classification | |
| varImp.gafs | Variable importances for GAs and SAs | |
| postResample | Calculates performance across resamples | |
| predict.knnreg | Predictions from k-Nearest Neighbors Regression Model | |
| rfe | Backwards Feature Selection | |
| plot.varImp.train | Plotting variable importance measures | |
| maxDissim | Maximum Dissimilarity Sampling | |
| oneSE | Selecting tuning Parameters | |
| varImp | Calculation of variable importance for regression and classification models | |
| confusionMatrix | Create a confusion matrix | |
| findCorrelation | Determine highly correlated variables | |
| oil | Fatty acid composition of commercial oils | |
| GermanCredit | German Credit Data | |
| caretSBF | Selection By Filtering (SBF) Helper Functions | |
| segmentationData | Cell Body Segmentation | |
| format.bagEarth | Format 'bagEarth' objects | |
| predict.bagEarth | Predicted values based on bagged Earth and FDA models | |
| train_model_list | A List of Available Models in train | |
| sensitivity | Calculate sensitivity, specificity and predictive values | |
| spatialSign | Compute the multivariate spatial sign | |
| findLinearCombos | Determine linear combinations in a matrix | |
| plot.gafs | Plot Method for the gafs and safs Classes | |
| bagEarth | Bagged Earth | |
| gafs.default | Genetic algorithm feature selection | |
| safs_initial | Ancillary simulated annealing functions | |
| update.safs | Update or Re-fit a SA or GA Model | |
| pcaNNet.default | Neural Networks with a Principal Component Step | |
| panel.lift2 | Lattice Panel Functions for Lift Plots | |
| plotObsVsPred | Plot Observed versus Predicted Results in Regression and Classification Models | |
| plot.train | Plot Method for the train Class | |
| resampleHist | Plot the resampling distribution of the model statistics | |
| safsControl | Control parameters for GA and SA feature selection | |
| downSample | Down- and Up-Sampling Imbalanced Data | |
| train | Fit Predictive Models over Different Tuning Parameters | |
| No Results! | ||
Last month downloads
Details
| Date | 2015-10-06 |
| URL | https://github.com/topepo/caret/ |
| BugReports | https://github.com/topepo/caret/issues |
| License | GPL (>= 2) |
| NeedsCompilation | yes |
| Packaged | 2015-10-09 20:15:43 UTC; kuhna03 |
| Repository | CRAN |
| Date/Publication | 2015-10-11 10:37:32 |
| 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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