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caret (version 4.17)

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

231,168

Version

4.17

License

GPL-2

Maintainer

Max Kuhn

Last Published

June 5th, 2009

Functions in caret (4.17)

predictors

List predictors used in the model
histogram.train

Lattice functions for plotting resampling results
confusionMatrix

Create a confusion matrix
findCorrelation

Determine highly correlated variables
preProcess

Pre-Processing of Predictors
caret-internal

Internal Functions
dotPlot

Create a dotplot of variable importance values
classDist

Compute and predict the distances to class centroids
bagEarth

Bagged Earth
bagFDA

Bagged FDA
cox2

COX-2 Activity Data
BloodBrain

Blood Brain Barrier Data
normalize2Reference

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

Summary of resampled performance estimates
mdrr

Multidrug Resistance Reversal (MDRR) Agent Data
panel.needle

Needle Plot Lattice Panel
format.bagEarth

Format 'bagEarth' objects
predict.train

Extract predictions and class probabilities from train objects
findLinearCombos

Determine linear combinations in a matrix
featurePlot

Wrapper for Lattice Plotting of Predictor Variables
maxDissim

Maximum Dissimilarity Sampling
pottery

Pottery from Pre-Classical Sites in Italy
plotClassProbs

Plot Predicted Probabilities in Classification Models
predict.bagEarth

Predicted values based on bagged Earth and FDA models
oil

Fatty acid composition of commercial oils
postResample

Calculates performance across resamples
createDataPartition

Data Splitting functions
rfeControl

Controlling the Feature Selection Algorithms
plsda

Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
plotObsVsPred

Plot Observed versus Predicted Results in Regression and Classification Models
knnreg

k-Nearest Neighbour Regression
knn3

k-Nearest Neighbour Classification
Alternate Affy Gene Expression Summary Methods.

Generate Expression Values from Probes
createGrid

Tuning Parameter Grid
resampleHist

Plot the resampling distribution of the model statistics
plot.train

Plot Method for the train Class
pcaNNet.default

Neural Networks with a Principal Component Step
print.train

Print Method for the train Class
aucRoc

Compute the area under an ROC curve
normalize.AffyBatch.normalize2Reference

Quantile Normalization to a Reference Distribution
plot.varImp.train

Plotting variable importance measures
tecator

Fat, Water and Protein Content of Maat Samples
predict.knn3

Predictions from k-Nearest Neighbors
lattice.rfe

Lattice functions for plotting resampling results of recursive feature selection
varImp

Calculation of variable importance for regression and classification models
roc

Compute the points for an ROC curve
nearZeroVar

Identification of near zero variance predictors
predict.knnreg

Predictions from k-Nearest Neighbors Regression Model
applyProcessing

Data Processing on Predictor Variables (Deprecated)
spatialSign

Compute the multivariate spatial sign
filterVarImp

Calculation of filter-based variable importance
train

Fit Predictive Models over Different Tuning Parameters
sensitivity

Calculate sensitivity, specificity and predictive values
print.confusionMatrix

Print method for confusionMatrix
rfe

Backwards Feature Selection
as.table.confusionMatrix

Save Confusion Table Results
oneSE

Selecting tuning Parameters
trainControl

Control parameters for train
summary.bagEarth

Summarize a bagged earth or FDA fit