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caret (version 4.63)
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
138,220
Version
4.63
License
GPL-2
Maintainer
Max Kuhn
Last Published
September 29th, 2010
Functions in caret (4.63)
Search all functions
bagEarth
Bagged Earth
confusionMatrix
Create a confusion matrix
format.bagEarth
Format 'bagEarth' objects
oil
Fatty acid composition of commercial oils
filterVarImp
Calculation of filter-based variable importance
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
knn3
k-Nearest Neighbour Classification
histogram.train
Lattice functions for plotting resampling results
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
caretFuncs
Backwards Feature Selection Helper Functions
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
resamples
Collation and Visualization of Resampling Results
resampleSummary
Summary of resampled performance estimates
caretSBF
Selection By Filtering (SBF) Helper Functions
spatialSign
Compute the multivariate spatial sign
sensitivity
Calculate sensitivity, specificity and predictive values
train
Fit Predictive Models over Different Tuning Parameters
classDist
Compute and predict the distances to class centroids
predict.train
Extract predictions and class probabilities from train objects
icr.formula
Independent Component Regression
findLinearCombos
Determine linear combinations in a matrix
prcomp.resamples
Principal Components Analysis of Resampling Results
summary.bagEarth
Summarize a bagged earth or FDA fit
tecator
Fat, Water and Protein Content of Meat Samples
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
knnreg
k-Nearest Neighbour Regression
predict.bagEarth
Predicted values based on bagged Earth and FDA models
applyProcessing
Data Processing on Predictor Variables (Deprecated)
as.table.confusionMatrix
Save Confusion Table Results
createDataPartition
Data Splitting functions
createGrid
Tuning Parameter Grid
dhfr
Dihydrofolate Reductase Inhibitors Data
GermanCredit
German Credit Data
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
plot.varImp.train
Plotting variable importance measures
caret-internal
Internal Functions
maxDissim
Maximum Dissimilarity Sampling
pottery
Pottery from Pre-Classical Sites in Italy
modelLookup
Descriptions Of Models Available in train()
postResample
Calculates performance across resamples
print.confusionMatrix
Print method for confusionMatrix
sbf
Selection By Filtering (SBF)
sbfControl
Control Object for Selection By Filtering (SBF)
plot.train
Plot Method for the train Class
plotClassProbs
Plot Predicted Probabilities in Classification Models
print.train
Print Method for the train Class
rfe
Backwards Feature Selection
varImp
Calculation of variable importance for regression and classification models
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
bag.default
A General Framework For Bagging
pcaNNet.default
Neural Networks with a Principal Component Step
oneSE
Selecting tuning Parameters
cars
Kelly Blue Book resale data for 2005 model year GM cars
dotPlot
Create a dotplot of variable importance values
findCorrelation
Determine highly correlated variables
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
nullModel
Fit a simple, non-informative model
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
BloodBrain
Blood Brain Barrier Data
aucRoc
Compute the area under an ROC curve
cox2
COX-2 Activity Data
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
preProcess
Pre-Processing of Predictors
predictors
List predictors used in the model
roc
Compute the points for an ROC curve
predict.knn3
Predictions from k-Nearest Neighbors
bagFDA
Bagged FDA
nearZeroVar
Identification of near zero variance predictors
diff.resamples
Inferential Assessments About Model Performance
rfeControl
Controlling the Feature Selection Algorithms
trainControl
Control parameters for train
panel.needle
Needle Plot Lattice Panel
resampleHist
Plot the resampling distribution of the model statistics