caret v4.24

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