caret v4.36

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