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caret (version 4.75)

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

4.75

License

GPL-2

Maintainer

Max Kuhn

Last Published

January 3rd, 2011

Functions in caret (4.75)

aucRoc

Compute the area under an ROC curve
predict.bagEarth

Predicted values based on bagged Earth and FDA models
filterVarImp

Calculation of filter-based variable importance
nearZeroVar

Identification of near zero variance predictors
dotplot.diff.resamples

Lattice Functions for Visualizing Resampling Differences
as.table.confusionMatrix

Save Confusion Table Results
dhfr

Dihydrofolate Reductase Inhibitors Data
panel.needle

Needle Plot Lattice Panel
bagEarth

Bagged Earth
bagFDA

Bagged FDA
plotClassProbs

Plot Predicted Probabilities in Classification Models
nullModel

Fit a simple, non-informative model
dummyVars

Create A Full Set of Dummy Variables
pottery

Pottery from Pre-Classical Sites in Italy
findLinearCombos

Determine linear combinations in a matrix
preProcess

Pre-Processing of Predictors
BloodBrain

Blood Brain Barrier Data
modelLookup

Descriptions Of Models Available in train()
rfe

Backwards Feature Selection
createDataPartition

Data Splitting functions
lattice.rfe

Lattice functions for plotting resampling results of recursive feature selection
resampleHist

Plot the resampling distribution of the model statistics
resamples

Collation and Visualization of Resampling Results
maxDissim

Maximum Dissimilarity Sampling
cox2

COX-2 Activity Data
postResample

Calculates performance across resamples
featurePlot

Wrapper for Lattice Plotting of Predictor Variables
print.confusionMatrix

Print method for confusionMatrix
createGrid

Tuning Parameter Grid
plsda

Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
predict.knn3

Predictions from k-Nearest Neighbors
normalize.AffyBatch.normalize2Reference

Quantile Normalization to a Reference Distribution
predict.knnreg

Predictions from k-Nearest Neighbors Regression Model
plot.varImp.train

Plotting variable importance measures
confusionMatrix

Create a confusion matrix
applyProcessing

Data Processing on Predictor Variables (Deprecated)
prcomp.resamples

Principal Components Analysis of Resampling Results
xyplot.resamples

Lattice Functions for Visualizing Resampling Results
knn3

k-Nearest Neighbour Classification
plotObsVsPred

Plot Observed versus Predicted Results in Regression and Classification Models
Alternate Affy Gene Expression Summary Methods.

Generate Expression Values from Probes
GermanCredit

German Credit Data
predict.train

Extract predictions and class probabilities from train objects
classDist

Compute and predict the distances to class centroids
diff.resamples

Inferential Assessments About Model Performance
bag.default

A General Framework For Bagging
dotPlot

Create a dotplot of variable importance values
normalize2Reference

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

Multidrug Resistance Reversal (MDRR) Agent Data
pcaNNet.default

Neural Networks with a Principal Component Step
cars

Kelly Blue Book resale data for 2005 model year GM cars
caret-internal

Internal Functions
oil

Fatty acid composition of commercial oils
print.train

Print Method for the train Class
caretFuncs

Backwards Feature Selection Helper Functions
knnreg

k-Nearest Neighbour Regression
caretSBF

Selection By Filtering (SBF) Helper Functions
format.bagEarth

Format 'bagEarth' objects
findCorrelation

Determine highly correlated variables
icr.formula

Independent Component Regression
resampleSummary

Summary of resampled performance estimates
predictors

List predictors used in the model
trainControl

Control parameters for train
sbf

Selection By Filtering (SBF)
tecator

Fat, Water and Protein Content of Meat Samples
sbfControl

Control Object for Selection By Filtering (SBF)
summary.bagEarth

Summarize a bagged earth or FDA fit
train

Fit Predictive Models over Different Tuning Parameters
segmentationData

Cell Body Segmentation
sensitivity

Calculate sensitivity, specificity and predictive values
spatialSign

Compute the multivariate spatial sign
oneSE

Selecting tuning Parameters
varImp

Calculation of variable importance for regression and classification models
rfeControl

Controlling the Feature Selection Algorithms
roc

Compute the points for an ROC curve
histogram.train

Lattice functions for plotting resampling results
plot.train

Plot Method for the train Class