caret v4.12


Monthly downloads



by Max Kuhn

Classification and Regression Training

Misc functions for training and plotting classification and regression models

Functions in caret

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

Last month downloads


Include our badge in your README