caret v4.19


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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
BloodBrain Blood Brain Barrier Data
lattice.rfe Lattice functions for plotting resampling results of recursive feature selection
mdrr Multidrug Resistance Reversal (MDRR) Agent Data
plsda Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
findCorrelation Determine highly correlated variables
applyProcessing Data Processing on Predictor Variables (Deprecated)
as.table.confusionMatrix Save Confusion Table Results
confusionMatrix Create a confusion matrix
knn3 k-Nearest Neighbour Classification
createDataPartition Data Splitting functions
createGrid Tuning Parameter Grid
bagFDA Bagged FDA
classDist Compute and predict the distances to class centroids
bagEarth Bagged Earth
aucRoc Compute the area under an ROC curve
cox2 COX-2 Activity Data
plot.varImp.train Plotting variable importance measures
featurePlot Wrapper for Lattice Plotting of Predictor Variables
predict.train Extract predictions and class probabilities from train objects
dotPlot Create a dotplot of variable importance values
panel.needle Needle Plot Lattice Panel
predict.knnreg Predictions from k-Nearest Neighbors Regression Model
rfe Backwards Feature Selection Helper Functions
normalize2Reference Quantile Normalize Columns of a Matrix Based on a Reference Distribution
maxDissim Maximum Dissimilarity Sampling
pottery Pottery from Pre-Classical Sites in Italy
caret-internal Internal Functions
predict.knn3 Predictions from k-Nearest Neighbors
filterVarImp Calculation of filter-based variable importance
trainControl Control parameters for train
postResample Calculates performance across resamples
histogram.train Lattice functions for plotting resampling results
resampleSummary Summary of resampled performance estimates
plot.train Plot Method for the train Class
print.train Print Method for the train Class
pcaNNet.default Neural Networks with a Principal Component Step
tecator Fat, Water and Protein Content of Maat Samples
predict.bagEarth Predicted values based on bagged Earth and FDA models
findLinearCombos Determine linear combinations in a matrix
print.confusionMatrix Print method for confusionMatrix
plotObsVsPred Plot Observed versus Predicted Results in Regression and Classification Models
nearZeroVar Identification of near zero variance predictors
oil Fatty acid composition of commercial oils
rfeControl Controlling the Feature Selection Algorithms
roc Compute the points for an ROC curve
knnreg k-Nearest Neighbour Regression
Alternate Affy Gene Expression Summary Methods. Generate Expression Values from Probes
predictors List predictors used in the model
summary.bagEarth Summarize a bagged earth or FDA fit
format.bagEarth Format 'bagEarth' objects
normalize.AffyBatch.normalize2Reference Quantile Normalization to a Reference Distribution
preProcess Pre-Processing of Predictors
plotClassProbs Plot Predicted Probabilities in Classification Models
train Fit Predictive Models over Different Tuning Parameters
oneSE Selecting tuning Parameters
resampleHist Plot the resampling distribution of the model statistics
spatialSign Compute the multivariate spatial sign
sensitivity Calculate sensitivity, specificity and predictive values
varImp Calculation of variable importance for regression and classification models
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