# caret v6.0-83

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## Classification and Regression Training

Misc functions for training and plotting classification and
regression models.

## Functions in caret

Name | Description | |

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

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

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

index2vec | Convert indicies to a binary vector | |

dummyVars | Create A Full Set of Dummy Variables | |

knn3 | k-Nearest Neighbour Classification | |

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

oil | Fatty acid composition of commercial oils | |

predict.gafs | Predict new samples | |

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

sbf | Selection By Filtering (SBF) | |

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

trainControl | Control parameters for train | |

SLC14_1 | Simulation Functions | |

GermanCredit | German Credit Data | |

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

bag | A General Framework For Bagging | |

bagEarth | Bagged Earth | |

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

confusionMatrix | Create a confusion matrix | |

dotPlot | Create a dotplot of variable importance values | |

Sacramento | Sacramento CA Home Prices | |

knnreg | k-Nearest Neighbour Regression | |

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

dhfr | Dihydrofolate Reductase Inhibitors Data | |

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

diff.resamples | Inferential Assessments About Model Performance | |

learning_curve_dat | Create Data to Plot a Learning Curve | |

lift | Lift Plot | |

caret-internal | Internal Functions | |

maxDissim | Maximum Dissimilarity Sampling | |

pickSizeBest | Backwards Feature Selection Helper Functions | |

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

findCorrelation | Determine highly correlated variables | |

BloodBrain | Blood Brain Barrier Data | |

BoxCoxTrans | Box-Cox and Exponential Transformations | |

cox2 | COX-2 Activity Data | |

confusionMatrix.train | Estimate a Resampled Confusion Matrix | |

featurePlot | Wrapper for Lattice Plotting of Predictor Variables | |

filterVarImp | Calculation of filter-based variable importance | |

icr.formula | Independent Component Regression | |

findLinearCombos | Determine linear combinations in a matrix | |

oneSE | Selecting tuning Parameters | |

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

defaultSummary | Calculates performance across resamples | |

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

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

gafs_initial | Ancillary genetic algorithm functions | |

bagFDA | Bagged FDA | |

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

train_model_list | A List of Available Models in train | |

getSamplingInfo | Get sampling info from a train model | |

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

nearZeroVar | Identification of near zero variance predictors | |

ggplot.rfe | Plot RFE Performance Profiles | |

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

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

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

modelLookup | Tools for Models Available in train | |

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

thresholder | Generate Data to Choose a Probability Threshold | |

recall | Calculate recall, precision and F values | |

train | Fit Predictive Models over Different Tuning Parameters | |

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

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

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

rfeControl | Controlling the Feature Selection Algorithms | |

panel.needle | Needle Plot Lattice Panel | |

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

pcaNNet | Neural Networks with a Principal Component Step | |

preProcess | Pre-Processing of Predictors | |

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

safs | Simulated annealing feature selection | |

calibration | Probability Calibration Plot | |

format.bagEarth | Format 'bagEarth' objects | |

scat | Morphometric Data on Scat | |

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

resamples | Collation and Visualization of Resampling Results | |

segmentationData | Cell Body Segmentation | |

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

safs_initial | Ancillary simulated annealing functions | |

rfe | Backwards Feature Selection | |

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

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

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

var_seq | Sequences of Variables for Tuning | |

gafs.default | Genetic algorithm feature selection | |

plotClassProbs | Plot Predicted Probabilities in Classification Models | |

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

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

predictors | List predictors used in the model | |

print.confusionMatrix | Print method for confusionMatrix | |

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

resampleSummary | Summary of resampled performance estimates | |

negPredValue | Calculate sensitivity, specificity and predictive values | |

spatialSign | Compute the multivariate spatial sign | |

createDataPartition | Data Splitting functions | |

avNNet | Neural Networks Using Model Averaging | |

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 | 2019-04-18 15:57:26 UTC; max |

Repository | CRAN |

Date/Publication | 2019-04-18 21:40:03 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 (>= 3.5.0) |

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 |

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