caret v4.59

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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
as.table.confusionMatrix Save Confusion Table Results
bag.default A General Framework For Bagging
normalize2Reference Quantile Normalize Columns of a Matrix Based on a Reference Distribution
cox2 COX-2 Activity Data
knnreg k-Nearest Neighbour Regression
spatialSign Compute the multivariate spatial sign
confusionMatrix Create a confusion matrix
predict.train Extract predictions and class probabilities from train objects
normalize.AffyBatch.normalize2Reference Quantile Normalization to a Reference Distribution
BloodBrain Blood Brain Barrier Data
predict.knn3 Predictions from k-Nearest Neighbors
trainControl Control parameters for train
findLinearCombos Determine linear combinations in a matrix
format.bagEarth Format 'bagEarth' objects
resamples Collation and Visualization of Resampling Results
resampleHist Plot the resampling distribution of the model statistics
sbfControl Control Object for Selection By Filtering (SBF)
tecator Fat, Water and Protein Content of Meat Samples
caretSBF Selection By Filtering (SBF) Helper Functions
bagEarth Bagged Earth
knn3 k-Nearest Neighbour Classification
featurePlot Wrapper for Lattice Plotting of Predictor Variables
xyplot.resamples Lattice Functions for Visualizing Resampling Results
modelLookup Descriptions Of Models Available in train()
predict.bagEarth Predicted values based on bagged Earth and FDA models
preProcess Pre-Processing of Predictors
oneSE Selecting tuning Parameters
createGrid Tuning Parameter Grid
plsda Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
rfe Backwards Feature Selection
sbf Selection By Filtering (SBF)
summary.bagEarth Summarize a bagged earth or FDA fit
classDist Compute and predict the distances to class centroids
nullModel Fit a simple, non-informative model
roc Compute the points for an ROC curve
pcaNNet.default Neural Networks with a Principal Component Step
predict.knnreg Predictions from k-Nearest Neighbors Regression Model
caret-internal Internal Functions
Alternate Affy Gene Expression Summary Methods. Generate Expression Values from Probes
maxDissim Maximum Dissimilarity Sampling
mdrr Multidrug Resistance Reversal (MDRR) Agent Data
filterVarImp Calculation of filter-based variable importance
findCorrelation Determine highly correlated variables
print.confusionMatrix Print method for confusionMatrix
plot.train Plot Method for the train Class
rfeControl Controlling the Feature Selection Algorithms
sensitivity Calculate sensitivity, specificity and predictive values
varImp Calculation of variable importance for regression and classification models
train Fit Predictive Models over Different Tuning Parameters
applyProcessing Data Processing on Predictor Variables (Deprecated)
bagFDA Bagged FDA
dhfr Dihydrofolate Reductase Inhibitors Data
icr.formula Independent Component Regression
dotplot.diff.resamples Lattice Functions for Visualizing Resampling Differences
plot.varImp.train Plotting variable importance measures
prcomp.resamples Principal Components Analysis of Resampling Results
oil Fatty acid composition of commercial oils
postResample Calculates performance across resamples
print.train Print Method for the train Class
caretFuncs Backwards Feature Selection Helper Functions
nearZeroVar Identification of near zero variance predictors
diff.resamples Inferential Assessments About Model Performance
panel.needle Needle Plot Lattice Panel
pottery Pottery from Pre-Classical Sites in Italy
resampleSummary Summary of resampled performance estimates
GermanCredit German Credit Data
cars Kelly Blue Book resale data for 2005 model year GM cars
createDataPartition Data Splitting functions
dotPlot Create a dotplot of variable importance values
histogram.train Lattice functions for plotting resampling results
lattice.rfe Lattice functions for plotting resampling results of recursive feature selection
plotClassProbs Plot Predicted Probabilities in Classification Models
predictors List predictors used in the model
plotObsVsPred Plot Observed versus Predicted Results in Regression and Classification Models
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