LASSO Logistic Regression for Binary Classification

Performs LASSO-penalized logistic regression for variable selection in binary classification problems. Supports LASSO, Ridge, and Elastic Net penalties. Includes suitability assessment, bootstrap validation, ROC analysis, and automated scoring system generation.

Super classes

jmvcore::Analysis -> ClinicoPath::lassologisticBase -> lassologisticClass

Methods

Public methods

• lassologisticClass$clone()

Inherited methods

• jmvcore::Analysis$.createImage()
• jmvcore::Analysis$.createImages()
• jmvcore::Analysis$.createPlotObject()
• jmvcore::Analysis$.load()
• jmvcore::Analysis$.render()
• jmvcore::Analysis$.save()
• jmvcore::Analysis$.savePart()
• jmvcore::Analysis$.setCheckpoint()
• jmvcore::Analysis$.setParent()
• jmvcore::Analysis$.setReadDatasetHeaderSource()
• jmvcore::Analysis$.setReadDatasetSource()
• jmvcore::Analysis$.setResourcesPathSource()
• jmvcore::Analysis$.setStatePathSource()
• jmvcore::Analysis$addAddon()
• jmvcore::Analysis$asProtoBuf()
• jmvcore::Analysis$asSource()
• jmvcore::Analysis$check()
• jmvcore::Analysis$init()
• jmvcore::Analysis$optionsChangedHandler()
• jmvcore::Analysis$postInit()
• jmvcore::Analysis$print()
• jmvcore::Analysis$readDataset()
• jmvcore::Analysis$run()
• jmvcore::Analysis$serialize()
• jmvcore::Analysis$setError()
• jmvcore::Analysis$setStatus()
• jmvcore::Analysis$translate()
• ClinicoPath::lassologisticBase$initialize()

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Method clone()

The objects of this class are cloneable with this method.

Usage

lassologisticClass$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.