caret v3.32

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