caret v5.01-001

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