caret v4.85

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