caret v4.26


Monthly downloads



by Max Kuhn

Classification and Regression Training

Misc functions for training and plotting classification and regression models

Functions in caret

Name Description
normalize.AffyBatch.normalize2Reference Quantile Normalization to a Reference Distribution
bagFDA Bagged FDA
plotClassProbs Plot Predicted Probabilities in Classification Models
as.table.confusionMatrix Save Confusion Table Results
filterVarImp Calculation of filter-based variable importance
caretFuncs Backwards Feature Selection Helper Functions
predict.bagEarth Predicted values based on bagged Earth and FDA models
histogram.train Lattice functions for plotting resampling results
maxDissim Maximum Dissimilarity Sampling
bagEarth Bagged Earth
print.train Print Method for the train Class
findLinearCombos Determine linear combinations in a matrix
roc Compute the points for an ROC curve
cox2 COX-2 Activity Data
rfeControl Controlling the Feature Selection Algorithms
findCorrelation Determine highly correlated variables
applyProcessing Data Processing on Predictor Variables (Deprecated)
plsda Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
lattice.rfe Lattice functions for plotting resampling results of recursive feature selection
mdrr Multidrug Resistance Reversal (MDRR) Agent Data
format.bagEarth Format 'bagEarth' objects
featurePlot Wrapper for Lattice Plotting of Predictor Variables
createDataPartition Data Splitting functions
predictors List predictors used in the model
createGrid Tuning Parameter Grid
resampleHist Plot the resampling distribution of the model statistics
summary.bagEarth Summarize a bagged earth or FDA fit
dotPlot Create a dotplot of variable importance values
pcaNNet.default Neural Networks with a Principal Component Step
knn3 k-Nearest Neighbour Classification
Alternate Affy Gene Expression Summary Methods. Generate Expression Values from Probes
panel.needle Needle Plot Lattice Panel
pottery Pottery from Pre-Classical Sites in Italy
classDist Compute and predict the distances to class centroids
BloodBrain Blood Brain Barrier Data
plotObsVsPred Plot Observed versus Predicted Results in Regression and Classification Models
aucRoc Compute the area under an ROC curve
tecator Fat, Water and Protein Content of Maat Samples
confusionMatrix Create a confusion matrix
train Fit Predictive Models over Different Tuning Parameters
knnreg k-Nearest Neighbour Regression
nearZeroVar Identification of near zero variance predictors
predict.train Extract predictions and class probabilities from train objects
print.confusionMatrix Print method for confusionMatrix
caret-internal Internal Functions
oil Fatty acid composition of commercial oils
varImp Calculation of variable importance for regression and classification models
plot.train Plot Method for the train Class
normalize2Reference Quantile Normalize Columns of a Matrix Based on a Reference Distribution
oneSE Selecting tuning Parameters
resampleSummary Summary of resampled performance estimates
trainControl Control parameters for train
postResample Calculates performance across resamples
sensitivity Calculate sensitivity, specificity and predictive values
preProcess Pre-Processing of Predictors
predict.knn3 Predictions from k-Nearest Neighbors
rfe Backwards Feature Selection
predict.knnreg Predictions from k-Nearest Neighbors Regression Model
plot.varImp.train Plotting variable importance measures
spatialSign Compute the multivariate spatial sign
No Results!

Last month downloads


Include our badge in your README