caret v5.15-052

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