Physical Sciences and Mathematics Commons^™

Drift Detection Using Uncertainty Distribution Divergence, Patrick Lindstrom, Brian Mac Namee, Sarah Jane Delany

Conference papers

Concept drift is believed to be prevalent inmost data gathered from naturally occurring processes andthus warrants research by the machine learning community.There are a myriad of approaches to concept drift handlingwhich have been shown to handle concept drift with varyingdegrees of success.

However, most approaches make the keyassumption that the labelled data will be available at nolabelling cost shortly after classification, an assumption whichis often violated. The high labelling cost in many domainsprovides a strong motivation to reduce the number of labelledinstances required to handle concept drift. Explicit detectionapproaches that do not require labelled instances to detectconcept drift show great …