caret v4.06


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