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caret (version 2.27)

Classification and Regression Training

Description

Misc functions for training and plotting classification and regression models

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Install

install.packages('caret')

Monthly Downloads

208,749

Version

2.27

License

GPL 2.0

Maintainer

Last Published

March 21st, 2023

Functions in caret (2.27)

oil

Fatty acid composition of commercial oils
findCorrelation

Determine highly correlated variables
filterVarImp

Calculation of filter-based variable importance
maxDissim

Maximum Dissimilarity Sampling
plotClassProbs

Plot Predicted Probabilities in Classification Models
bagFDA

Bagged FDA
tecator

Fat, Water and Protein Content of Maat Samples
plot.varImp.train

Plotting variable importance measures
plsda

Partial Least Squares Discriminant Analysis
print.train

Print Method for the train Class
createDataPartition

Data Splitting functions
cox2

COX-2 Activity Data
normalize2Reference

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

Bagged Earth
predict.bagEarth

Predicted values based on bagged Earth and FDA models
print.confusionMatrix

Print method for confusionMatrix
plotObsVsPred

Plot Observed versus Predicted Results in Regression and Classification Models
trainControl

Control parameters for train
Alternate Affy Gene Expression Summary Methods.

Generate Expression Values from Probes
confusionMatrix

Create a confusion matrix
applyProcessing

Data Processing on Predictor Variables
caret-internal

Internal Functions
findLinearCombos

Determine linear combinations in a matrix
aucRoc

Compute the area under an ROC curve
plot.train

Plot Method for the train Class
varImp

Calculation of variable importance for regression and classification models
panel.needle

Needle Plot Lattice Panel
spatialSign

Compute the multivariate spatial sign
extractPrediction

Extract predictions and class probabilities from train objects
resampleHist

Plot the resampling distribution of the model statistics
postResample

Calculates performance across resamples
resampleSummary

Summary of resampled performance estimates
dotPlot

Create a dotplot of variable importance values
featurePlot

Wrapper for Lattice Plotting of Predictor Variables
predict.knn3

Predictions from k-Nearest Neighbors
summary.bagEarth

Summarize a bagged earth or FDA fit
knn3

k-Nearest Neighbour Classification
createGrid

Tuning Parameter Grid
normalize.AffyBatch.normalize2Reference

Quantile Normalization to a Reference Distribution
sensitivity

Calculate Sensitivity, Specificity and predictive values
train

Fit Predictive Models over Different Tuning Parameters
nearZeroVar

Identification of near zero variance predictors
pottery

Pottery from Pre-Classical Sites in Italy
roc

Compute the points for an ROC curve
BloodBrain

Blood Brain Barrier Data
mdrr

Multidrug Resistance Reversal (MDRR) Agent Data