caret v4.87

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