caret v4.44


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