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caret (version 3.25)

Classification and Regression Training

Description

Misc functions for training and plotting classification and regression models

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Version

Install

install.packages('caret')

Monthly Downloads

163,965

Version

3.25

License

GPL-2

Maintainer

Max Kuhn

Last Published

December 10th, 2024

Functions in caret (3.25)

caret-internal

Internal Functions
findLinearCombos

Determine linear combinations in a matrix
bagFDA

Bagged FDA
BloodBrain

Blood Brain Barrier Data
filterVarImp

Calculation of filter-based variable importance
predict.bagEarth

Predicted values based on bagged Earth and FDA models
postResample

Calculates performance across resamples
confusionMatrix

Create a confusion matrix
plotObsVsPred

Plot Observed versus Predicted Results in Regression and Classification Models
applyProcessing

Data Processing on Predictor Variables (Deprecated)
resampleSummary

Summary of resampled performance estimates
print.confusionMatrix

Print method for confusionMatrix
createGrid

Tuning Parameter Grid
plotClassProbs

Plot Predicted Probabilities in Classification Models
dotPlot

Create a dotplot of variable importance values
format.bagEarth

Format 'bagEarth' objects
cox2

COX-2 Activity Data
plot.varImp.train

Plotting variable importance measures
oil

Fatty acid composition of commercial oils
resampleHist

Plot the resampling distribution of the model statistics
extractPrediction

Extract predictions and class probabilities from train objects
plsda

Partial Least Squares Discriminant Analysis
bagEarth

Bagged Earth
pottery

Pottery from Pre-Classical Sites in Italy
aucRoc

Compute the area under an ROC curve
spatialSign

Compute the multivariate spatial sign
summary.bagEarth

Summarize a bagged earth or FDA fit
varImp

Calculation of variable importance for regression and classification models
createDataPartition

Data Splitting functions
sensitivity

Calculate Sensitivity, Specificity and predictive values
featurePlot

Wrapper for Lattice Plotting of Predictor Variables
nearZeroVar

Identification of near zero variance predictors
trainControl

Control parameters for train
Alternate Affy Gene Expression Summary Methods.

Generate Expression Values from Probes
predict.knn3

Predictions from k-Nearest Neighbors
panel.needle

Needle Plot Lattice Panel
print.train

Print Method for the train Class
tecator

Fat, Water and Protein Content of Maat Samples
findCorrelation

Determine highly correlated variables
maxDissim

Maximum Dissimilarity Sampling
normalize2Reference

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

Compute the points for an ROC curve
normalize.AffyBatch.normalize2Reference

Quantile Normalization to a Reference Distribution
train

Fit Predictive Models over Different Tuning Parameters
plot.train

Plot Method for the train Class
pcaNNet.default

Neural Networks with a Principal Component Step
mdrr

Multidrug Resistance Reversal (MDRR) Agent Data
oneSE

Selecting tuning Parameters
preProcess

Pre-Processing of Predictors
knn3

k-Nearest Neighbour Classification