caret v5.16-04

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