caret v4.23

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