Learn R Programming

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

caret (version 3.51)

Classification and Regression Training

Description

Misc functions for training and plotting classification and regression models

Copy Link

Version

Install

install.packages('caret')

Monthly Downloads

230,598

Version

3.51

License

GPL-2

Maintainer

Max Kuhn

Last Published

December 10th, 2024

Functions in caret (3.51)

predict.knn3

Predictions from k-Nearest Neighbors
predict.train

Extract predictions and class probabilities from train objects
bagEarth

Bagged Earth
knn3

k-Nearest Neighbour Classification
dotPlot

Create a dotplot of variable importance values
print.confusionMatrix

Print method for confusionMatrix
plsda

Partial Least Squares Discriminant Analysis
nearZeroVar

Identification of near zero variance predictors
print.train

Print Method for the train Class
normalize.AffyBatch.normalize2Reference

Quantile Normalization to a Reference Distribution
roc

Compute the points for an ROC curve
normalize2Reference

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

Tuning Parameter Grid
format.bagEarth

Format 'bagEarth' objects
plot.varImp.train

Plotting variable importance measures
Alternate Affy Gene Expression Summary Methods.

Generate Expression Values from Probes
applyProcessing

Data Processing on Predictor Variables (Deprecated)
BloodBrain

Blood Brain Barrier Data
preProcess

Pre-Processing of Predictors
resampleSummary

Summary of resampled performance estimates
panel.needle

Needle Plot Lattice Panel
oil

Fatty acid composition of commercial oils
trainControl

Control parameters for train
train

Fit Predictive Models over Different Tuning Parameters
spatialSign

Compute the multivariate spatial sign
confusionMatrix

Create a confusion matrix
mdrr

Multidrug Resistance Reversal (MDRR) Agent Data
plot.train

Plot Method for the train Class
sensitivity

Calculate Sensitivity, Specificity and predictive values
featurePlot

Wrapper for Lattice Plotting of Predictor Variables
predict.bagEarth

Predicted values based on bagged Earth and FDA models
pcaNNet.default

Neural Networks with a Principal Component Step
filterVarImp

Calculation of filter-based variable importance
pottery

Pottery from Pre-Classical Sites in Italy
resampleHist

Plot the resampling distribution of the model statistics
varImp

Calculation of variable importance for regression and classification models
summary.bagEarth

Summarize a bagged earth or FDA fit
maxDissim

Maximum Dissimilarity Sampling
bagFDA

Bagged FDA
oneSE

Selecting tuning Parameters
postResample

Calculates performance across resamples
createDataPartition

Data Splitting functions
aucRoc

Compute the area under an ROC curve
caret-internal

Internal Functions
predictors

List predictors used in the model
histogram.train

Lattice functions for plotting resampling results
plotClassProbs

Plot Predicted Probabilities in Classification Models
findCorrelation

Determine highly correlated variables
plotObsVsPred

Plot Observed versus Predicted Results in Regression and Classification Models
findLinearCombos

Determine linear combinations in a matrix
tecator

Fat, Water and Protein Content of Maat Samples
cox2

COX-2 Activity Data