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caret (version 4.62)

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

230,598

Version

4.62

License

GPL-2

Maintainer

Max Kuhn

Last Published

September 10th, 2010

Functions in caret (4.62)

aucRoc

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

Save Confusion Table Results
format.bagEarth

Format 'bagEarth' objects
dotplot.diff.resamples

Lattice Functions for Visualizing Resampling Differences
print.train

Print Method for the train Class
resamples

Collation and Visualization of Resampling Results
plotObsVsPred

Plot Observed versus Predicted Results in Regression and Classification Models
createDataPartition

Data Splitting functions
histogram.train

Lattice functions for plotting resampling results
cars

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

Pre-Processing of Predictors
predict.knnreg

Predictions from k-Nearest Neighbors Regression Model
oneSE

Selecting tuning Parameters
panel.needle

Needle Plot Lattice Panel
resampleSummary

Summary of resampled performance estimates
caretFuncs

Backwards Feature Selection Helper Functions
confusionMatrix

Create a confusion matrix
diff.resamples

Inferential Assessments About Model Performance
dotPlot

Create a dotplot of variable importance values
oil

Fatty acid composition of commercial oils
nearZeroVar

Identification of near zero variance predictors
predict.bagEarth

Predicted values based on bagged Earth and FDA models
caretSBF

Selection By Filtering (SBF) Helper Functions
icr.formula

Independent Component Regression
modelLookup

Descriptions Of Models Available in train()
nullModel

Fit a simple, non-informative model
plsda

Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
pcaNNet.default

Neural Networks with a Principal Component Step
mdrr

Multidrug Resistance Reversal (MDRR) Agent Data
resampleHist

Plot the resampling distribution of the model statistics
prcomp.resamples

Principal Components Analysis of Resampling Results
findCorrelation

Determine highly correlated variables
rfeControl

Controlling the Feature Selection Algorithms
bagFDA

Bagged FDA
predict.train

Extract predictions and class probabilities from train objects
maxDissim

Maximum Dissimilarity Sampling
normalize2Reference

Quantile Normalize Columns of a Matrix Based on a Reference Distribution
normalize.AffyBatch.normalize2Reference

Quantile Normalization to a Reference Distribution
pottery

Pottery from Pre-Classical Sites in Italy
GermanCredit

German Credit Data
predictors

List predictors used in the model
bag.default

A General Framework For Bagging
predict.knn3

Predictions from k-Nearest Neighbors
featurePlot

Wrapper for Lattice Plotting of Predictor Variables
sbf

Selection By Filtering (SBF)
cox2

COX-2 Activity Data
plotClassProbs

Plot Predicted Probabilities in Classification Models
spatialSign

Compute the multivariate spatial sign
sensitivity

Calculate sensitivity, specificity and predictive values
varImp

Calculation of variable importance for regression and classification models
tecator

Fat, Water and Protein Content of Meat Samples
summary.bagEarth

Summarize a bagged earth or FDA fit
knnreg

k-Nearest Neighbour Regression
BloodBrain

Blood Brain Barrier Data
bagEarth

Bagged Earth
createGrid

Tuning Parameter Grid
findLinearCombos

Determine linear combinations in a matrix
plot.varImp.train

Plotting variable importance measures
postResample

Calculates performance across resamples
rfe

Backwards Feature Selection
roc

Compute the points for an ROC curve
trainControl

Control parameters for train
dhfr

Dihydrofolate Reductase Inhibitors Data
applyProcessing

Data Processing on Predictor Variables (Deprecated)
Alternate Affy Gene Expression Summary Methods.

Generate Expression Values from Probes
knn3

k-Nearest Neighbour Classification
lattice.rfe

Lattice functions for plotting resampling results of recursive feature selection
plot.train

Plot Method for the train Class
sbfControl

Control Object for Selection By Filtering (SBF)
xyplot.resamples

Lattice Functions for Visualizing Resampling Results
train

Fit Predictive Models over Different Tuning Parameters
caret-internal

Internal Functions
filterVarImp

Calculation of filter-based variable importance
classDist

Compute and predict the distances to class centroids
print.confusionMatrix

Print method for confusionMatrix