caret v4.16

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