Man pages for zachmayer/caretEnsemble
Ensembles of Caret Models

aggregate_mean_or_firstAggregate mean or first
as.caretListConvert object to caretList object
as.caretList.defaultConvert object to caretList object - For Future Use
as.caretList.listConvert list to caretList
autoplot.caretStackConvenience function for more in-depth diagnostic plots of...
caretEnsembleCombine several predictive models via weights
caretListCreate a list of several train models from the caret package
caretModelSpecGenerate a specification for fitting a caret model
caretPredictPrediction wrapper for 'train'
caretStackCombine several predictive models via stacking
caretTrainWrapper to train caret models
c.caretListS3 definition for concatenating caretList
check_caretStackCheck caretStack object
checkCustomModelValidate a custom caret model info list
c.trainS3 definition for concatenating train objects
defaultControlConstruct a default train control for use with caretList
defaultMetricConstruct a default metric
dotplot.caretStackComparison dotplot for a caretStack object
dropExcludedClassDrop Excluded Class
extractBestPredsExtract the best predictions from a train object
extractCaretTargetExtracts the target variable from a set of arguments headed...
extractCaretTarget.defaultExtracts the target variable from a set of arguments headed...
extractCaretTarget.formulaExtracts the target variable from a set of arguments headed...
extractMetricGeneric function to extract accuracy metrics from various...
extractMetric.caretListExtract accuracy metrics from a 'caretList' object
extractMetric.caretStackExtract accuracy metrics from a 'caretStack' object
extractMetric.trainExtract accuracy metrics from a 'train' model
extractModelNameExtract the method name associated with a single train object
greedyMSEGreedy optimization for MSE
greedyMSE_caretcaret interface for greedyMSE
isClassifierIs Classifier
isClassifierAndValidateValidate a model type
maeCompute MAE
methodCheckCheck that the methods supplied by the user are valid caret...
models.classcaretList of classification models
models.regcaretList of regression models
normalize_to_oneNormalize to One
permutationImportancePermutation Importance
plot.caretListPlot a caretList object
plot.caretStackPlot a caretStack object
predict.caretListCreate a matrix of predictions for each of the models in a...
predict.caretStackMake predictions from a caretStack
predict.greedyMSEPredict method for greedyMSE
print.caretStackPrint a caretStack object
print.greedyMSEPrint method for greedyMSE
print.summary.caretListPrint a summary.caretList object
print.summary.caretStackPrint a summary.caretStack object
set_excluded_class_idSet excluded class id
shuffled_maeShuffled MAE
stackedTrainResidualsExtracted stacked residuals for the autoplot
sub-.caretListIndex a caretList
summary.caretListSummarize a caretList
summary.caretStackSummarize a caretStack object
tuneCheckCheck that the tuning parameters list supplied by the user is...
validateExcludedClassValidate the excluded class
varImp.caretStackVariable importance for caretStack
varImp.greedyMSEvariable importance for a greedyMSE model
wtd.sdCalculate a weighted standard deviation
X.classdata for classification
X.regdata for classification
Y.classdata for classification
Y.regdata for regression
zachmayer/caretEnsemble documentation built on Sept. 13, 2024, 7:53 p.m.