caret v4.37

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