caret v4.10


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