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caret (version 4.47)

Classification and Regression Training

Description

Misc functions for training and plotting classification and regression models

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Install

install.packages('caret')

Monthly Downloads

148,125

Version

4.47

License

GPL-2

Maintainer

Last Published

August 5th, 2010

Functions in caret (4.47)

GermanCredit

German Credit Data
predictors

List predictors used in the model
mdrr

Multidrug Resistance Reversal (MDRR) Agent Data
cars

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

Fit Predictive Models over Different Tuning Parameters
knnreg

k-Nearest Neighbour Regression
xyplot.resamples

Lattice Functions for Visualizing Resampling Results
createDataPartition

Data Splitting functions
createGrid

Tuning Parameter Grid
findLinearCombos

Determine linear combinations in a matrix
as.table.confusionMatrix

Save Confusion Table Results
Alternate Affy Gene Expression Summary Methods.

Generate Expression Values from Probes
BloodBrain

Blood Brain Barrier Data
roc

Compute the points for an ROC curve
applyProcessing

Data Processing on Predictor Variables (Deprecated)
oil

Fatty acid composition of commercial oils
diff.resamples

Inferential Assessments About Model Performance
lattice.rfe

Lattice functions for plotting resampling results of recursive feature selection
nullModel

Fit a simple, non-informative model
spatialSign

Compute the multivariate spatial sign
oneSE

Selecting tuning Parameters
dotPlot

Create a dotplot of variable importance values
trainControl

Control parameters for train
predict.train

Extract predictions and class probabilities from train objects
resamples

Collation and Visualization of Resampling Results
caretFuncs

Backwards Feature Selection Helper Functions
normalize.AffyBatch.normalize2Reference

Quantile Normalization to a Reference Distribution
rfe

Backwards Feature Selection
sensitivity

Calculate sensitivity, specificity and predictive values
sbfControl

Control Object for Selection By Filtering (SBF)
confusionMatrix

Create a confusion matrix
plotObsVsPred

Plot Observed versus Predicted Results in Regression and Classification Models
findCorrelation

Determine highly correlated variables
predict.bagEarth

Predicted values based on bagged Earth and FDA models
caret-internal

Internal Functions
classDist

Compute and predict the distances to class centroids
dhfr

Dihydrofolate Reductase Inhibitors Data
histogram.train

Lattice functions for plotting resampling results
pcaNNet.default

Neural Networks with a Principal Component Step
resampleSummary

Summary of resampled performance estimates
plotClassProbs

Plot Predicted Probabilities in Classification Models
caretSBF

Selection By Filtering (SBF) Helper Functions
tecator

Fat, Water and Protein Content of Meat Samples
varImp

Calculation of variable importance for regression and classification models
bag.default

A General Framework For Bagging
predict.knnreg

Predictions from k-Nearest Neighbors Regression Model
print.confusionMatrix

Print method for confusionMatrix
print.train

Print Method for the train Class
preProcess

Pre-Processing of Predictors
postResample

Calculates performance across resamples
bagEarth

Bagged Earth
plot.train

Plot Method for the train Class
sbf

Selection By Filtering (SBF)
cox2

COX-2 Activity Data
resampleHist

Plot the resampling distribution of the model statistics
plsda

Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
format.bagEarth

Format 'bagEarth' objects
plot.varImp.train

Plotting variable importance measures
bagFDA

Bagged FDA
aucRoc

Compute the area under an ROC curve
dotplot.diff.resamples

Lattice Functions for Visualizing Resampling Differences
icr.formula

Independent Component Regression
nearZeroVar

Identification of near zero variance predictors
knn3

k-Nearest Neighbour Classification
pottery

Pottery from Pre-Classical Sites in Italy
featurePlot

Wrapper for Lattice Plotting of Predictor Variables
filterVarImp

Calculation of filter-based variable importance
maxDissim

Maximum Dissimilarity Sampling
normalize2Reference

Quantile Normalize Columns of a Matrix Based on a Reference Distribution
predict.knn3

Predictions from k-Nearest Neighbors
panel.needle

Needle Plot Lattice Panel
rfeControl

Controlling the Feature Selection Algorithms
summary.bagEarth

Summarize a bagged earth or FDA fit