caret v5.08-011


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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
nullModel Fit a simple, non-informative model
rfe Backwards Feature Selection
caret-internal Internal Functions
aucRoc Compute the area under an ROC curve
oil Fatty acid composition of commercial oils
dotPlot Create a dotplot of variable importance values
findLinearCombos Determine linear combinations in a matrix
plot.varImp.train Plotting variable importance measures
cox2 COX-2 Activity Data
plotObsVsPred Plot Observed versus Predicted Results in Regression and Classification Models
xyplot.resamples Lattice Functions for Visualizing Resampling Results
rfeControl Controlling the Feature Selection Algorithms
BloodBrain Blood Brain Barrier Data
prcomp.resamples Principal Components Analysis of Resampling Results
modelLookup Descriptions Of Models Available in train()
resampleHist Plot the resampling distribution of the model statistics
plot.train Plot Method for the train Class
normalize2Reference Quantile Normalize Columns of a Matrix Based on a Reference Distribution
sbfControl Control Object for Selection By Filtering (SBF)
as.table.confusionMatrix Save Confusion Table Results
classDist Compute and predict the distances to class centroids
bagFDA Bagged FDA
bag.default A General Framework For Bagging
histogram.train Lattice functions for plotting resampling results
plsda Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
pottery Pottery from Pre-Classical Sites in Italy
dummyVars Create A Full Set of Dummy Variables
preProcess Pre-Processing of Predictors
panel.lift2 Lattice Panel Functions for Lift Plots
nearZeroVar Identification of near zero variance predictors
confusionMatrix.train Estimate a Resampled Confusion Matrix
createDataPartition Data Splitting functions
dhfr Dihydrofolate Reductase Inhibitors Data
oneSE Selecting tuning Parameters
resamples Collation and Visualization of Resampling Results
confusionMatrix Create a confusion matrix
format.bagEarth Format 'bagEarth' objects
plotClassProbs Plot Predicted Probabilities in Classification Models
filterVarImp Calculation of filter-based variable importance
Alternate Affy Gene Expression Summary Methods. Generate Expression Values from Probes
featurePlot Wrapper for Lattice Plotting of Predictor Variables
pcaNNet.default Neural Networks with a Principal Component Step
panel.needle Needle Plot Lattice Panel
mdrr Multidrug Resistance Reversal (MDRR) Agent Data
print.confusionMatrix Print method for confusionMatrix
sensitivity Calculate sensitivity, specificity and predictive values
findCorrelation Determine highly correlated variables
dotplot.diff.resamples Lattice Functions for Visualizing Resampling Differences
BoxCoxTrans.default Box-Cox Transformations
predict.knnreg Predictions from k-Nearest Neighbors Regression Model
postResample Calculates performance across resamples
segmentationData Cell Body Segmentation
train Fit Predictive Models over Different Tuning Parameters
trainControl Control parameters for train
caretFuncs Backwards Feature Selection Helper Functions
resampleSummary Summary of resampled performance estimates
caretSBF Selection By Filtering (SBF) Helper Functions
varImp Calculation of variable importance for regression and classification models
cars Kelly Blue Book resale data for 2005 model year GM cars
maxDissim Maximum Dissimilarity Sampling
predict.knn3 Predictions from k-Nearest Neighbors
lattice.rfe Lattice functions for plotting resampling results of recursive feature selection
avNNet.default Neural Networks Using Model Averaging
knnreg k-Nearest Neighbour Regression
summary.bagEarth Summarize a bagged earth or FDA fit
spatialSign Compute the multivariate spatial sign
icr.formula Independent Component Regression
roc Compute the points for an ROC curve
tecator Fat, Water and Protein Content of Meat Samples
sbf Selection By Filtering (SBF)
predict.bagEarth Predicted values based on bagged Earth and FDA models
diff.resamples Inferential Assessments About Model Performance
createGrid Tuning Parameter Grid
lift Lift Plot
predictors List predictors used in the model
print.train Print Method for the train Class
bagEarth Bagged Earth
normalize.AffyBatch.normalize2Reference Quantile Normalization to a Reference Distribution
knn3 k-Nearest Neighbour Classification
GermanCredit German Credit Data
predict.train Extract predictions and class probabilities from train objects
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