caret v4.20


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