# caret v6.0-84

0

Monthly downloads

## Classification and Regression Training

Misc functions for training and plotting classification and
regression models.

## Functions in caret

Name | Description | |

confusionMatrix.train | Estimate a Resampled Confusion Matrix | |

gafs_initial | Ancillary genetic algorithm functions | |

BloodBrain | Blood Brain Barrier Data | |

getSamplingInfo | Get sampling info from a train model | |

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

createDataPartition | Data Splitting functions | |

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

oneSE | Selecting tuning Parameters | |

findLinearCombos | Determine linear combinations in a matrix | |

findCorrelation | Determine highly correlated variables | |

cox2 | COX-2 Activity Data | |

dotPlot | Create a dotplot of variable importance values | |

knnreg | k-Nearest Neighbour Regression | |

BoxCoxTrans | Box-Cox and Exponential Transformations | |

dhfr | Dihydrofolate Reductase Inhibitors Data | |

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

pickSizeBest | Backwards Feature Selection Helper Functions | |

Sacramento | Sacramento CA Home Prices | |

diff.resamples | Inferential Assessments About Model Performance | |

caret-internal | Internal Functions | |

featurePlot | Wrapper for Lattice Plotting of Predictor Variables | |

modelLookup | Tools for Models Available in train | |

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

index2vec | Convert indicies to a binary vector | |

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

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

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

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

filterVarImp | Calculation of filter-based variable importance | |

learning_curve_dat | Create Data to Plot a Learning Curve | |

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

icr.formula | Independent Component Regression | |

lift | Lift Plot | |

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

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

knn3 | k-Nearest Neighbour Classification | |

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

defaultSummary | Calculates performance across resamples | |

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

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

maxDissim | Maximum Dissimilarity Sampling | |

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

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

preProcess | Pre-Processing of Predictors | |

predict.gafs | Predict new samples | |

dummyVars | Create A Full Set of Dummy Variables | |

predict.bagEarth | Predicted values based on bagged Earth and FDA models | |

format.bagEarth | Format 'bagEarth' objects | |

gafs.default | Genetic algorithm feature selection | |

train_model_list | A List of Available Models in train | |

nearZeroVar | Identification of near zero variance predictors | |

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

predict.knn3 | Predictions from k-Nearest Neighbors | |

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

oil | Fatty acid composition of commercial oils | |

panel.needle | Needle Plot Lattice Panel | |

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

plotClassProbs | Plot Predicted Probabilities in Classification Models | |

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

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

pcaNNet | Neural Networks with a Principal Component Step | |

safs_initial | Ancillary simulated annealing functions | |

scat | Morphometric Data on Scat | |

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

ggplot.rfe | Plot RFE Performance Profiles | |

segmentationData | Cell Body Segmentation | |

predict.knnreg | Predictions from k-Nearest Neighbors Regression Model | |

trainControl | Control parameters for train | |

extractPrediction | Extract predictions and class probabilities from train objects | |

recall | Calculate recall, precision and F values | |

resamples | Collation and Visualization of Resampling Results | |

predictors | List predictors used in the model | |

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

SLC14_1 | Simulation Functions | |

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

resampleSummary | Summary of resampled performance estimates | |

sbf | Selection By Filtering (SBF) | |

rfe | Backwards Feature Selection | |

print.confusionMatrix | Print method for confusionMatrix | |

negPredValue | Calculate sensitivity, specificity and predictive values | |

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

spatialSign | Compute the multivariate spatial sign | |

rfeControl | Controlling the Feature Selection Algorithms | |

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

safs | Simulated annealing feature selection | |

var_seq | Sequences of Variables for Tuning | |

thresholder | Generate Data to Choose a Probability Threshold | |

train | Fit Predictive Models over Different Tuning Parameters | |

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

as.matrix.confusionMatrix | Confusion matrix as a table | |

GermanCredit | German Credit Data | |

bag | A General Framework For Bagging | |

bagEarth | Bagged Earth | |

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

confusionMatrix | Create a confusion matrix | |

avNNet | Neural Networks Using Model Averaging | |

bagFDA | Bagged FDA | |

calibration | Probability Calibration Plot | |

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 | 6.1.1 |

VignetteBuilder | knitr |

Encoding | UTF-8 |

NeedsCompilation | yes |

Packaged | 2019-04-26 14:30:05 UTC; max |

Repository | CRAN |

Date/Publication | 2019-04-27 04:50:03 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 (>= 0.1.4) , reshape2 , stats , stats4 , utils , withr (>= 2.0.0) |

depends | ggplot2 , lattice (>= 0.20) , R (>= 3.2.0) |

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 |

#### Include our badge in your README

```
[![Rdoc](http://www.rdocumentation.org/badges/version/caret)](http://www.rdocumentation.org/packages/caret)
```