caret v6.0-80
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Classification and Regression Training
Misc functions for training and plotting classification and
regression models.
Functions in caret
| Name | Description | |
| cars | Kelly Blue Book resale data for 2005 model year GM cars | |
| dhfr | Dihydrofolate Reductase Inhibitors Data | |
| gafs_initial | Ancillary genetic algorithm functions | |
| densityplot.rfe | Lattice functions for plotting resampling results of recursive feature selection | |
| getSamplingInfo | Get sampling info from a train model | |
| recall | Calculate recall, precision and F values | |
| print.train | Print Method for the train Class | |
| print.confusionMatrix | Print method for confusionMatrix | |
| plot.varImp.train | Plotting variable importance measures | |
| lift | Lift Plot | |
| predictors | List predictors used in the model | |
| findLinearCombos | Determine linear combinations in a matrix | |
| maxDissim | Maximum Dissimilarity Sampling | |
| findCorrelation | Determine highly correlated variables | |
| histogram.train | Lattice functions for plotting resampling results | |
| ggplot.train | Plot Method for the train Class | |
| nearZeroVar | Identification of near zero variance predictors | |
| icr.formula | Independent Component Regression | |
| plot.gafs | Plot Method for the gafs and safs Classes | |
| train_model_list | A List of Available Models in train | |
| downSample | Down- and Up-Sampling Imbalanced Data | |
| featurePlot | Wrapper for Lattice Plotting of Predictor Variables | |
| diff.resamples | Inferential Assessments About Model Performance | |
| predict.gafs | Predict new samples | |
| filterVarImp | Calculation of filter-based variable importance | |
| thresholder | Generate Data to Choose a Probability Threshold | |
| dummyVars | Create A Full Set of Dummy Variables | |
| format.bagEarth | Format 'bagEarth' objects | |
| gafs.default | Genetic algorithm feature selection | |
| nullModel | Fit a simple, non-informative model | |
| dotplot.diff.resamples | Lattice Functions for Visualizing Resampling Differences | |
| knnreg | k-Nearest Neighbour Regression | |
| oil | Fatty acid composition of commercial oils | |
| knn3 | k-Nearest Neighbour Classification | |
| dotPlot | Create a dotplot of variable importance values | |
| learing_curve_dat | Create Data to Plot a Learning Curve | |
| index2vec | Convert indicies to a binary vector | |
| oneSE | Selecting tuning Parameters | |
| train | Fit Predictive Models over Different Tuning Parameters | |
| mdrr | Multidrug Resistance Reversal (MDRR) Agent Data | |
| ggplot.rfe | Plot RFE Performance Profiles | |
| modelLookup | Tools for Models Available in train | |
| pottery | Pottery from Pre-Classical Sites in Italy | |
| plotClassProbs | Plot Predicted Probabilities in Classification Models | |
| pcaNNet | Neural Networks with a Principal Component Step | |
| preProcess | Pre-Processing of Predictors | |
| predict.knn3 | Predictions from k-Nearest Neighbors | |
| varImp.gafs | Variable importances for GAs and SAs | |
| predict.bagEarth | Predicted values based on bagged Earth and FDA models | |
| panel.lift2 | Lattice Panel Functions for Lift Plots | |
| varImp | Calculation of variable importance for regression and classification models | |
| panel.needle | Needle Plot Lattice Panel | |
| plsda | Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis | |
| summary.bagEarth | Summarize a bagged earth or FDA fit | |
| resampleHist | Plot the resampling distribution of the model statistics | |
| defaultSummary | Calculates performance across resamples | |
| tecator | Fat, Water and Protein Content of Meat Samples | |
| plotObsVsPred | Plot Observed versus Predicted Results in Regression and Classification Models | |
| predict.knnreg | Predictions from k-Nearest Neighbors Regression Model | |
| extractPrediction | Extract predictions and class probabilities from train objects | |
| update.safs | Update or Re-fit a SA or GA Model | |
| safs | Simulated annealing feature selection | |
| rfeControl | Controlling the Feature Selection Algorithms | |
| resamples | Collation and Visualization of Resampling Results | |
| update.train | Update or Re-fit a Model | |
| negPredValue | Calculate sensitivity, specificity and predictive values | |
| prcomp.resamples | Principal Components Analysis of Resampling Results | |
| resampleSummary | Summary of resampled performance estimates | |
| segmentationData | Cell Body Segmentation | |
| safs_initial | Ancillary simulated annealing functions | |
| scat | Morphometric Data on Scat | |
| gafsControl | Control parameters for GA and SA feature selection | |
| spatialSign | Compute the multivariate spatial sign | |
| rfe | Backwards Feature Selection | |
| sbf | Selection By Filtering (SBF) | |
| sbfControl | Control Object for Selection By Filtering (SBF) | |
| var_seq | Sequences of Variables for Tuning | |
| xyplot.resamples | Lattice Functions for Visualizing Resampling Results | |
| trainControl | Control parameters for train | |
| SLC14_1 | Simulation Functions | |
| createDataPartition | Data Splitting functions | |
| bag | A General Framework For Bagging | |
| as.matrix.confusionMatrix | Confusion matrix as a table | |
| bagFDA | Bagged FDA | |
| avNNet | Neural Networks Using Model Averaging | |
| classDist | Compute and predict the distances to class centroids | |
| calibration | Probability Calibration Plot | |
| caret-internal | Internal Functions | |
| BloodBrain | Blood Brain Barrier Data | |
| pickSizeBest | Backwards Feature Selection Helper Functions | |
| confusionMatrix | Create a confusion matrix | |
| BoxCoxTrans | Box-Cox and Exponential Transformations | |
| bagEarth | Bagged Earth | |
| caretSBF | Selection By Filtering (SBF) Helper Functions | |
| GermanCredit | German Credit Data | |
| Sacramento | Sacramento CA Home Prices | |
| confusionMatrix.train | Estimate a Resampled Confusion Matrix | |
| cox2 | COX-2 Activity Data | |
| No Results! | ||
Vignettes of caret
| Name | ||
| caret.Rmd | ||
| train_algo.png | ||
| No Results! | ||
Last month downloads
Details
| URL | https://github.com/topepo/caret/ |
| BugReports | https://github.com/topepo/caret/issues |
| License | GPL (>= 2) |
| RoxygenNote | 6.0.1 |
| VignetteBuilder | knitr |
| NeedsCompilation | yes |
| Packaged | 2018-05-26 15:05:02 UTC; max |
| Repository | CRAN |
| Date/Publication | 2018-05-26 22:01:28 UTC |
| suggests | BradleyTerry2 , Cubist , dplyr , e1071 , earth (>= 2.2-3) , ellipse , fastICA , gam (>= 1.15) , ipred , kernlab , klaR , knitr , MASS , mda , mgcv , mlbench , MLmetrics , nnet , pamr , party (>= 0.9-99992) , pls , pROC , proxy , randomForest , RANN , rpart , spls , subselect , superpc , testthat (>= 0.9.1) |
| imports | foreach , grDevices , methods , ModelMetrics (>= 1.1.0) , nlme , plyr , recipes (>= 0.0.1) , reshape2 , stats , stats4 , utils , withr (>= 2.0.0) |
| depends | ggplot2 , lattice (>= 0.20) , R (>= 2.10) |
| Contributors | the Core team, Brenton Kenkel, Max Contributions from Jed Wing, Steve Weston, Andre Williams, Chris Keefer, Allan Engelhardt, Tyler Hunt, Tony Cooper, Zachary Mayer, Michael Benesty, Reynald Lescarbeau, Andrew Ziem, Luca Scrucca, Yuan Tang, Can Candan |
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