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caret (version 4.59)

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

4.59

License

GPL-2

Maintainer

Max Kuhn

Last Published

September 1st, 2010

Functions in caret (4.59)

aucRoc

Compute the area under an ROC curve
as.table.confusionMatrix

Save Confusion Table Results
bag.default

A General Framework For Bagging
normalize2Reference

Quantile Normalize Columns of a Matrix Based on a Reference Distribution
cox2

COX-2 Activity Data
knnreg

k-Nearest Neighbour Regression
spatialSign

Compute the multivariate spatial sign
confusionMatrix

Create a confusion matrix
predict.train

Extract predictions and class probabilities from train objects
normalize.AffyBatch.normalize2Reference

Quantile Normalization to a Reference Distribution
BloodBrain

Blood Brain Barrier Data
predict.knn3

Predictions from k-Nearest Neighbors
trainControl

Control parameters for train
findLinearCombos

Determine linear combinations in a matrix
format.bagEarth

Format 'bagEarth' objects
resamples

Collation and Visualization of Resampling Results
resampleHist

Plot the resampling distribution of the model statistics
sbfControl

Control Object for Selection By Filtering (SBF)
tecator

Fat, Water and Protein Content of Meat Samples
caretSBF

Selection By Filtering (SBF) Helper Functions
bagEarth

Bagged Earth
knn3

k-Nearest Neighbour Classification
featurePlot

Wrapper for Lattice Plotting of Predictor Variables
xyplot.resamples

Lattice Functions for Visualizing Resampling Results
modelLookup

Descriptions Of Models Available in train()
predict.bagEarth

Predicted values based on bagged Earth and FDA models
preProcess

Pre-Processing of Predictors
oneSE

Selecting tuning Parameters
createGrid

Tuning Parameter Grid
plsda

Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
rfe

Backwards Feature Selection
sbf

Selection By Filtering (SBF)
summary.bagEarth

Summarize a bagged earth or FDA fit
classDist

Compute and predict the distances to class centroids
nullModel

Fit a simple, non-informative model
roc

Compute the points for an ROC curve
pcaNNet.default

Neural Networks with a Principal Component Step
predict.knnreg

Predictions from k-Nearest Neighbors Regression Model
caret-internal

Internal Functions
Alternate Affy Gene Expression Summary Methods.

Generate Expression Values from Probes
maxDissim

Maximum Dissimilarity Sampling
mdrr

Multidrug Resistance Reversal (MDRR) Agent Data
filterVarImp

Calculation of filter-based variable importance
findCorrelation

Determine highly correlated variables
print.confusionMatrix

Print method for confusionMatrix
plot.train

Plot Method for the train Class
rfeControl

Controlling the Feature Selection Algorithms
sensitivity

Calculate sensitivity, specificity and predictive values
varImp

Calculation of variable importance for regression and classification models
train

Fit Predictive Models over Different Tuning Parameters
applyProcessing

Data Processing on Predictor Variables (Deprecated)
bagFDA

Bagged FDA
dhfr

Dihydrofolate Reductase Inhibitors Data
icr.formula

Independent Component Regression
dotplot.diff.resamples

Lattice Functions for Visualizing Resampling Differences
plot.varImp.train

Plotting variable importance measures
prcomp.resamples

Principal Components Analysis of Resampling Results
oil

Fatty acid composition of commercial oils
postResample

Calculates performance across resamples
print.train

Print Method for the train Class
caretFuncs

Backwards Feature Selection Helper Functions
nearZeroVar

Identification of near zero variance predictors
diff.resamples

Inferential Assessments About Model Performance
panel.needle

Needle Plot Lattice Panel
pottery

Pottery from Pre-Classical Sites in Italy
resampleSummary

Summary of resampled performance estimates
GermanCredit

German Credit Data
cars

Kelly Blue Book resale data for 2005 model year GM cars
createDataPartition

Data Splitting functions
dotPlot

Create a dotplot of variable importance values
histogram.train

Lattice functions for plotting resampling results
lattice.rfe

Lattice functions for plotting resampling results of recursive feature selection
plotClassProbs

Plot Predicted Probabilities in Classification Models
predictors

List predictors used in the model
plotObsVsPred

Plot Observed versus Predicted Results in Regression and Classification Models