caret v5.13-20

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by Max Kuhn

Classification and Regression Training

Misc functions for training and plotting classification and regression models

Functions in caret

Name Description
GermanCredit German Credit Data
plot.train Plot Method for the train Class
caret-internal Internal Functions
prcomp.resamples Principal Components Analysis of Resampling Results
bag.default A General Framework For Bagging
as.table.confusionMatrix Save Confusion Table Results
format.bagEarth Format 'bagEarth' objects
createGrid Tuning Parameter Grid
dotplot.diff.resamples Lattice Functions for Visualizing Resampling Differences
dotPlot Create a dotplot of variable importance values
featurePlot Wrapper for Lattice Plotting of Predictor Variables
calibration Probability Calibration Plot
BloodBrain Blood Brain Barrier Data
normalize.AffyBatch.normalize2Reference Quantile Normalization to a Reference Distribution
dhfr Dihydrofolate Reductase Inhibitors Data
BoxCoxTrans.default Box-Cox Transformations
mdrr Multidrug Resistance Reversal (MDRR) Agent Data
bagFDA Bagged FDA
resampleSummary Summary of resampled performance estimates
Alternate Affy Gene Expression Summary Methods. Generate Expression Values from Probes
diff.resamples Inferential Assessments About Model Performance
caretSBF Selection By Filtering (SBF) Helper Functions
histogram.train Lattice functions for plotting resampling results
spatialSign Compute the multivariate spatial sign
predict.bagEarth Predicted values based on bagged Earth and FDA models
lift Lift Plot
normalize2Reference Quantile Normalize Columns of a Matrix Based on a Reference Distribution
cars Kelly Blue Book resale data for 2005 model year GM cars
pcaNNet.default Neural Networks with a Principal Component Step
classDist Compute and predict the distances to class centroids
dummyVars Create A Full Set of Dummy Variables
avNNet.default Neural Networks Using Model Averaging
icr.formula Independent Component Regression
update.train Update and Re-fit a Model
predict.train Extract predictions and class probabilities from train objects
filterVarImp Calculation of filter-based variable importance
bagEarth Bagged Earth
oil Fatty acid composition of commercial oils
pottery Pottery from Pre-Classical Sites in Italy
xyplot.resamples Lattice Functions for Visualizing Resampling Results
knnreg k-Nearest Neighbour Regression
nullModel Fit a simple, non-informative model
panel.lift2 Lattice Panel Functions for Lift Plots
rfeControl Controlling the Feature Selection Algorithms
summary.bagEarth Summarize a bagged earth or FDA fit
resamples Collation and Visualization of Resampling Results
lattice.rfe Lattice functions for plotting resampling results of recursive feature selection
modelLookup Descriptions Of Models Available in train()
print.confusionMatrix Print method for confusionMatrix
plotObsVsPred Plot Observed versus Predicted Results in Regression and Classification Models
createDataPartition Data Splitting functions
cox2 COX-2 Activity Data
train Fit Predictive Models over Different Tuning Parameters
knn3 k-Nearest Neighbour Classification
predictors List predictors used in the model
varImp Calculation of variable importance for regression and classification models
plot.varImp.train Plotting variable importance measures
plotClassProbs Plot Predicted Probabilities in Classification Models
predict.knnreg Predictions from k-Nearest Neighbors Regression Model
findCorrelation Determine highly correlated variables
maxDissim Maximum Dissimilarity Sampling
postResample Calculates performance across resamples
tecator Fat, Water and Protein Content of Meat Samples
predict.knn3 Predictions from k-Nearest Neighbors
resampleHist Plot the resampling distribution of the model statistics
rfe Backwards Feature Selection
sbf Selection By Filtering (SBF)
findLinearCombos Determine linear combinations in a matrix
caretFuncs Backwards Feature Selection Helper Functions
nearZeroVar Identification of near zero variance predictors
print.train Print Method for the train Class
oneSE Selecting tuning Parameters
trainControl Control parameters for train
plsda Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
panel.needle Needle Plot Lattice Panel
preProcess Pre-Processing of Predictors
segmentationData Cell Body Segmentation
confusionMatrix Create a confusion matrix
confusionMatrix.train Estimate a Resampled Confusion Matrix
sensitivity Calculate sensitivity, specificity and predictive values
sbfControl Control Object for Selection By Filtering (SBF)
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