caret v4.18

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