caret v4.54

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