caret v5.15-048

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