caret v3.25

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