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caret (version 4.20)

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

4.20

License

GPL-2

Maintainer

Max Kuhn

Last Published

August 25th, 2009

Functions in caret (4.20)

confusionMatrix

Create a confusion matrix
bagFDA

Bagged FDA
resampleHist

Plot the resampling distribution of the model statistics
pottery

Pottery from Pre-Classical Sites in Italy
print.confusionMatrix

Print method for confusionMatrix
Alternate Affy Gene Expression Summary Methods.

Generate Expression Values from Probes
classDist

Compute and predict the distances to class centroids
spatialSign

Compute the multivariate spatial sign
maxDissim

Maximum Dissimilarity Sampling
trainControl

Control parameters for train
predict.train

Extract predictions and class probabilities from train objects
as.table.confusionMatrix

Save Confusion Table Results
lattice.rfe

Lattice functions for plotting resampling results of recursive feature selection
filterVarImp

Calculation of filter-based variable importance
aucRoc

Compute the area under an ROC curve
preProcess

Pre-Processing of Predictors
bagEarth

Bagged Earth
sensitivity

Calculate sensitivity, specificity and predictive values
plotClassProbs

Plot Predicted Probabilities in Classification Models
roc

Compute the points for an ROC curve
panel.needle

Needle Plot Lattice Panel
nearZeroVar

Identification of near zero variance predictors
normalize2Reference

Quantile Normalize Columns of a Matrix Based on a Reference Distribution
histogram.train

Lattice functions for plotting resampling results
knn3

k-Nearest Neighbour Classification
mdrr

Multidrug Resistance Reversal (MDRR) Agent Data
pcaNNet.default

Neural Networks with a Principal Component Step
normalize.AffyBatch.normalize2Reference

Quantile Normalization to a Reference Distribution
createDataPartition

Data Splitting functions
dotPlot

Create a dotplot of variable importance values
resampleSummary

Summary of resampled performance estimates
rfe

Backwards Feature Selection Helper Functions
predict.knn3

Predictions from k-Nearest Neighbors
oneSE

Selecting tuning Parameters
predict.bagEarth

Predicted values based on bagged Earth and FDA models
cox2

COX-2 Activity Data
varImp

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

Format 'bagEarth' objects
plot.train

Plot Method for the train Class
createGrid

Tuning Parameter Grid
knnreg

k-Nearest Neighbour Regression
findLinearCombos

Determine linear combinations in a matrix
predict.knnreg

Predictions from k-Nearest Neighbors Regression Model
print.train

Print Method for the train Class
summary.bagEarth

Summarize a bagged earth or FDA fit
tecator

Fat, Water and Protein Content of Maat Samples
caret-internal

Internal Functions
plot.varImp.train

Plotting variable importance measures
train

Fit Predictive Models over Different Tuning Parameters
findCorrelation

Determine highly correlated variables
plotObsVsPred

Plot Observed versus Predicted Results in Regression and Classification Models
rfeControl

Controlling the Feature Selection Algorithms
applyProcessing

Data Processing on Predictor Variables (Deprecated)
plsda

Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
BloodBrain

Blood Brain Barrier Data
featurePlot

Wrapper for Lattice Plotting of Predictor Variables
predictors

List predictors used in the model
postResample

Calculates performance across resamples
oil

Fatty acid composition of commercial oils