caret v5.13-037


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