caret v4.75

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