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caret (version 4.24)

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

158,845

Version

4.24

License

GPL-2

Maintainer

Max Kuhn

Last Published

September 30th, 2009

Functions in caret (4.24)

BloodBrain

Blood Brain Barrier Data
as.table.confusionMatrix

Save Confusion Table Results
panel.needle

Needle Plot Lattice Panel
Alternate Affy Gene Expression Summary Methods.

Generate Expression Values from Probes
format.bagEarth

Format 'bagEarth' objects
normalize2Reference

Quantile Normalize Columns of a Matrix Based on a Reference Distribution
pcaNNet.default

Neural Networks with a Principal Component Step
print.confusionMatrix

Print method for confusionMatrix
knn3

k-Nearest Neighbour Classification
predict.train

Extract predictions and class probabilities from train objects
caret-internal

Internal Functions
oil

Fatty acid composition of commercial oils
plot.train

Plot Method for the train Class
maxDissim

Maximum Dissimilarity Sampling
predict.bagEarth

Predicted values based on bagged Earth and FDA models
plsda

Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
createGrid

Tuning Parameter Grid
applyProcessing

Data Processing on Predictor Variables (Deprecated)
featurePlot

Wrapper for Lattice Plotting of Predictor Variables
knnreg

k-Nearest Neighbour Regression
plot.varImp.train

Plotting variable importance measures
findLinearCombos

Determine linear combinations in a matrix
findCorrelation

Determine highly correlated variables
resampleHist

Plot the resampling distribution of the model statistics
nearZeroVar

Identification of near zero variance predictors
oneSE

Selecting tuning Parameters
normalize.AffyBatch.normalize2Reference

Quantile Normalization to a Reference Distribution
filterVarImp

Calculation of filter-based variable importance
confusionMatrix

Create a confusion matrix
predict.knnreg

Predictions from k-Nearest Neighbors Regression Model
rfe

Backwards Feature Selection
rfeControl

Controlling the Feature Selection Algorithms
createDataPartition

Data Splitting functions
mdrr

Multidrug Resistance Reversal (MDRR) Agent Data
predictors

List predictors used in the model
spatialSign

Compute the multivariate spatial sign
sensitivity

Calculate sensitivity, specificity and predictive values
histogram.train

Lattice functions for plotting resampling results
plotClassProbs

Plot Predicted Probabilities in Classification Models
plotObsVsPred

Plot Observed versus Predicted Results in Regression and Classification Models
pottery

Pottery from Pre-Classical Sites in Italy
varImp

Calculation of variable importance for regression and classification models
bagFDA

Bagged FDA
predict.knn3

Predictions from k-Nearest Neighbors
classDist

Compute and predict the distances to class centroids
trainControl

Control parameters for train
train

Fit Predictive Models over Different Tuning Parameters
bagEarth

Bagged Earth
roc

Compute the points for an ROC curve
dotPlot

Create a dotplot of variable importance values
print.train

Print Method for the train Class
caretFuncs

Backwards Feature Selection Helper Functions
resampleSummary

Summary of resampled performance estimates
tecator

Fat, Water and Protein Content of Maat Samples
lattice.rfe

Lattice functions for plotting resampling results of recursive feature selection
postResample

Calculates performance across resamples
aucRoc

Compute the area under an ROC curve
cox2

COX-2 Activity Data
summary.bagEarth

Summarize a bagged earth or FDA fit
preProcess

Pre-Processing of Predictors