caret v4.61


Monthly downloads



by Max Kuhn

Classification and Regression Training

Misc functions for training and plotting classification and regression models

Functions in caret

Name Description
bagFDA Bagged FDA
classDist Compute and predict the distances to class centroids
confusionMatrix Create a confusion matrix
cox2 COX-2 Activity Data
nearZeroVar Identification of near zero variance predictors
predict.train Extract predictions and class probabilities from train objects
plot.train Plot Method for the train Class
rfeControl Controlling the Feature Selection Algorithms
dhfr Dihydrofolate Reductase Inhibitors Data
format.bagEarth Format 'bagEarth' objects
xyplot.resamples Lattice Functions for Visualizing Resampling Results
plot.varImp.train Plotting variable importance measures
predict.knn3 Predictions from k-Nearest Neighbors
caretSBF Selection By Filtering (SBF) Helper Functions
sbfControl Control Object for Selection By Filtering (SBF)
dotPlot Create a dotplot of variable importance values
featurePlot Wrapper for Lattice Plotting of Predictor Variables
mdrr Multidrug Resistance Reversal (MDRR) Agent Data
normalize2Reference Quantile Normalize Columns of a Matrix Based on a Reference Distribution
oil Fatty acid composition of commercial oils
maxDissim Maximum Dissimilarity Sampling
preProcess Pre-Processing of Predictors
roc Compute the points for an ROC curve
summary.bagEarth Summarize a bagged earth or FDA fit
normalize.AffyBatch.normalize2Reference Quantile Normalization to a Reference Distribution
train Fit Predictive Models over Different Tuning Parameters
print.confusionMatrix Print method for confusionMatrix
GermanCredit German Credit Data
knn3 k-Nearest Neighbour Classification
createGrid Tuning Parameter Grid
pcaNNet.default Neural Networks with a Principal Component Step
resampleSummary Summary of resampled performance estimates
sbf Selection By Filtering (SBF)
varImp Calculation of variable importance for regression and classification models
findLinearCombos Determine linear combinations in a matrix
predictors List predictors used in the model
resamples Collation and Visualization of Resampling Results
tecator Fat, Water and Protein Content of Meat Samples
caret-internal Internal Functions
findCorrelation Determine highly correlated variables
dotplot.diff.resamples Lattice Functions for Visualizing Resampling Differences
lattice.rfe Lattice functions for plotting resampling results of recursive feature selection
icr.formula Independent Component Regression
filterVarImp Calculation of filter-based variable importance
prcomp.resamples Principal Components Analysis of Resampling Results
sensitivity Calculate sensitivity, specificity and predictive values
caretFuncs Backwards Feature Selection Helper Functions
as.table.confusionMatrix Save Confusion Table Results
aucRoc Compute the area under an ROC curve
oneSE Selecting tuning Parameters
knnreg k-Nearest Neighbour Regression
plotObsVsPred Plot Observed versus Predicted Results in Regression and Classification Models
trainControl Control parameters for train
spatialSign Compute the multivariate spatial sign
resampleHist Plot the resampling distribution of the model statistics
postResample Calculates performance across resamples
rfe Backwards Feature Selection
predict.knnreg Predictions from k-Nearest Neighbors Regression Model
print.train Print Method for the train Class
applyProcessing Data Processing on Predictor Variables (Deprecated)
bagEarth Bagged Earth
cars Kelly Blue Book resale data for 2005 model year GM cars
Alternate Affy Gene Expression Summary Methods. Generate Expression Values from Probes
panel.needle Needle Plot Lattice Panel
nullModel Fit a simple, non-informative model
plotClassProbs Plot Predicted Probabilities in Classification Models
predict.bagEarth Predicted values based on bagged Earth and FDA models
BloodBrain Blood Brain Barrier Data
bag.default A General Framework For Bagging
createDataPartition Data Splitting functions
diff.resamples Inferential Assessments About Model Performance
histogram.train Lattice functions for plotting resampling results
modelLookup Descriptions Of Models Available in train()
pottery Pottery from Pre-Classical Sites in Italy
plsda Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
No Results!

Last month downloads


Include our badge in your README