caret v5.16-24

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