caret v4.60


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