caret v4.98


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