# caret v6.0-70

0

Monthly downloads

by Max Kuhn

## Classification and Regression Training

Misc functions for training and plotting classification and
regression models.

## Functions in caret

Name | Description | |

bag.default | A General Framework For Bagging | |

as.table.confusionMatrix | Save Confusion Table Results | |

cars | Kelly Blue Book resale data for 2005 model year GM cars | |

calibration | Probability Calibration Plot | |

BoxCoxTrans.default | Box-Cox and Exponential Transformations | |

caret-internal | Internal Functions | |

BloodBrain | Blood Brain Barrier Data | |

avNNet.default | Neural Networks Using Model Averaging | |

bagEarth | Bagged Earth | |

bagFDA | Bagged FDA | |

dummyVars | Create A Full Set of Dummy Variables | |

cox2 | COX-2 Activity Data | |

classDist | Compute and predict the distances to class centroids | |

createDataPartition | Data Splitting functions | |

predict.train | Extract predictions and class probabilities from train objects | |

dotPlot | Create a dotplot of variable importance values | |

confusionMatrix.train | Estimate a Resampled Confusion Matrix | |

dhfr | Dihydrofolate Reductase Inhibitors Data | |

downSample | Down- and Up-Sampling Imbalanced Data | |

diff.resamples | Inferential Assessments About Model Performance | |

format.bagEarth | Format 'bagEarth' objects | |

GermanCredit | German Credit Data | |

getSamplingInfo | Get sampling info from a train model | |

findLinearCombos | Determine linear combinations in a matrix | |

gafs_initial | Ancillary genetic algorithm functions | |

icr.formula | Independent Component Regression | |

gafs.default | Genetic algorithm feature selection | |

featurePlot | Wrapper for Lattice Plotting of Predictor Variables | |

findCorrelation | Determine highly correlated variables | |

filterVarImp | Calculation of filter-based variable importance | |

dotplot.diff.resamples | Lattice Functions for Visualizing Resampling Differences | |

lattice.rfe | Lattice functions for plotting resampling results of recursive feature selection | |

maxDissim | Maximum Dissimilarity Sampling | |

index2vec | Convert indicies to a binary vector | |

knnreg | k-Nearest Neighbour Regression | |

histogram.train | Lattice functions for plotting resampling results | |

learing_curve_dat | Create Data to Plot a Learning Curve | |

knn3 | k-Nearest Neighbour Classification | |

xyplot.resamples | Lattice Functions for Visualizing Resampling Results | |

lift | Lift Plot | |

nullModel | Fit a simple, non-informative model | |

panel.needle | Needle Plot Lattice Panel | |

modelLookup | Tools for Models Available in train | |

oil | Fatty acid composition of commercial oils | |

plot.gafs | Plot Method for the gafs and safs Classes | |

nearZeroVar | Identification of near zero variance predictors | |

pcaNNet.default | Neural Networks with a Principal Component Step | |

panel.lift2 | Lattice Panel Functions for Lift Plots | |

train_model_list | A List of Available Models in train | |

mdrr | Multidrug Resistance Reversal (MDRR) Agent Data | |

plot.rfe | Plot RFE Performance Profiles | |

plot.varImp.train | Plotting variable importance measures | |

prcomp.resamples | Principal Components Analysis of Resampling Results | |

plot.train | Plot Method for the train Class | |

pottery | Pottery from Pre-Classical Sites in Italy | |

plotClassProbs | Plot Predicted Probabilities in Classification Models | |

plotObsVsPred | Plot Observed versus Predicted Results in Regression and Classification Models | |

plsda | Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis | |

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 | |

resampleSummary | Summary of resampled performance estimates | |

var_seq | Sequences of Variables for Tuning | |

print.train | Print Method for the train Class | |

print.confusionMatrix | Print method for confusionMatrix | |

resampleHist | Plot the resampling distribution of the model statistics | |

resamples | Collation and Visualization of Resampling Results | |

predictors | List predictors used in the model | |

preProcess | Pre-Processing of Predictors | |

sbf | Selection By Filtering (SBF) | |

safsControl | Control parameters for GA and SA feature selection | |

sbfControl | Control Object for Selection By Filtering (SBF) | |

safs.default | Simulated annealing feature selection | |

Sacramento | Sacramento CA Home Prices | |

caretSBF | Selection By Filtering (SBF) Helper Functions | |

rfe | Backwards Feature Selection | |

rfeControl | Controlling the Feature Selection Algorithms | |

caretFuncs | Backwards Feature Selection Helper Functions | |

safs_initial | Ancillary simulated annealing functions | |

oneSE | Selecting tuning Parameters | |

segmentationData | Cell Body Segmentation | |

update.safs | Update or Re-fit a SA or GA Model | |

twoClassSim | Simulation Functions | |

tecator | Fat, Water and Protein Content of Meat Samples | |

trainControl | Control parameters for train | |

update.train | Update or Re-fit a Model | |

varImp.gafs | Variable importances for GAs and SAs | |

varImp | Calculation of variable importance for regression and classification models | |

spatialSign | Compute the multivariate spatial sign | |

summary.bagEarth | Summarize a bagged earth or FDA fit | |

No Results! |

## Last month downloads

## Details

Date | 2016-06-09 |

URL | https://github.com/topepo/caret/ |

BugReports | https://github.com/topepo/caret/issues |

License | GPL (>= 2) |

NeedsCompilation | yes |

Packaged | 2016-06-13 10:50:50 UTC; kuhna03 |

Repository | CRAN |

Date/Publication | 2016-06-13 16:03:41 |

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 , spls , subselect , superpc , testthat (>= 0.9.1) |

imports | car , foreach , grDevices , methods , nlme , plyr , reshape2 , stats , stats4 , utils |

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, Tony Cooper, Zachary Mayer, Michael Benesty, Reynald Lescarbeau, Andrew Ziem, Luca Scrucca, Yuan Tang, Can Candan |

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