caret v4.63

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