caret v6.0-22

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