caret v4.33

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