Learn R Programming

⚠️There's a newer version (7.0-1) of this package.Take me there.

caret (version 4.76)

Classification and Regression Training

Description

Misc functions for training and plotting classification and regression models

Copy Link

Version

Install

install.packages('caret')

Monthly Downloads

163,965

Version

4.76

License

GPL-2

Maintainer

Max Kuhn

Last Published

January 8th, 2011

Functions in caret (4.76)

createDataPartition

Data Splitting functions
diff.resamples

Inferential Assessments About Model Performance
normalize.AffyBatch.normalize2Reference

Quantile Normalization to a Reference Distribution
icr.formula

Independent Component Regression
oil

Fatty acid composition of commercial oils
postResample

Calculates performance across resamples
classDist

Compute and predict the distances to class centroids
knn3

k-Nearest Neighbour Classification
bagEarth

Bagged Earth
bagFDA

Bagged FDA
maxDissim

Maximum Dissimilarity Sampling
plotClassProbs

Plot Predicted Probabilities in Classification Models
as.table.confusionMatrix

Save Confusion Table Results
filterVarImp

Calculation of filter-based variable importance
GermanCredit

German Credit Data
modelLookup

Descriptions Of Models Available in train()
applyProcessing

Data Processing on Predictor Variables (Deprecated)
caret-internal

Internal Functions
bag.default

A General Framework For Bagging
aucRoc

Compute the area under an ROC curve
BloodBrain

Blood Brain Barrier Data
xyplot.resamples

Lattice Functions for Visualizing Resampling Results
confusionMatrix

Create a confusion matrix
histogram.train

Lattice functions for plotting resampling results
plot.varImp.train

Plotting variable importance measures
plotObsVsPred

Plot Observed versus Predicted Results in Regression and Classification Models
preProcess

Pre-Processing of Predictors
prcomp.resamples

Principal Components Analysis of Resampling Results
format.bagEarth

Format 'bagEarth' objects
plot.train

Plot Method for the train Class
lattice.rfe

Lattice functions for plotting resampling results of recursive feature selection
nearZeroVar

Identification of near zero variance predictors
resampleHist

Plot the resampling distribution of the model statistics
pcaNNet.default

Neural Networks with a Principal Component Step
createGrid

Tuning Parameter Grid
print.confusionMatrix

Print method for confusionMatrix
knnreg

k-Nearest Neighbour Regression
mdrr

Multidrug Resistance Reversal (MDRR) Agent Data
findLinearCombos

Determine linear combinations in a matrix
dotPlot

Create a dotplot of variable importance values
tecator

Fat, Water and Protein Content of Meat Samples
dhfr

Dihydrofolate Reductase Inhibitors Data
varImp

Calculation of variable importance for regression and classification models
predictors

List predictors used in the model
sensitivity

Calculate sensitivity, specificity and predictive values
resamples

Collation and Visualization of Resampling Results
predict.knn3

Predictions from k-Nearest Neighbors
sbfControl

Control Object for Selection By Filtering (SBF)
sbf

Selection By Filtering (SBF)
print.train

Print Method for the train Class
dotplot.diff.resamples

Lattice Functions for Visualizing Resampling Differences
summary.bagEarth

Summarize a bagged earth or FDA fit
pottery

Pottery from Pre-Classical Sites in Italy
cars

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

Fit Predictive Models over Different Tuning Parameters
predict.bagEarth

Predicted values based on bagged Earth and FDA models
nullModel

Fit a simple, non-informative model
oneSE

Selecting tuning Parameters
trainControl

Control parameters for train
caretSBF

Selection By Filtering (SBF) Helper Functions
spatialSign

Compute the multivariate spatial sign
predict.knnreg

Predictions from k-Nearest Neighbors Regression Model
roc

Compute the points for an ROC curve
resampleSummary

Summary of resampled performance estimates
plsda

Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
caretFuncs

Backwards Feature Selection Helper Functions
panel.needle

Needle Plot Lattice Panel
featurePlot

Wrapper for Lattice Plotting of Predictor Variables
Alternate Affy Gene Expression Summary Methods.

Generate Expression Values from Probes
segmentationData

Cell Body Segmentation
rfeControl

Controlling the Feature Selection Algorithms
findCorrelation

Determine highly correlated variables
rfe

Backwards Feature Selection
normalize2Reference

Quantile Normalize Columns of a Matrix Based on a Reference Distribution
cox2

COX-2 Activity Data
dummyVars

Create A Full Set of Dummy Variables
predict.train

Extract predictions and class probabilities from train objects