Burst detection-based selective classifier resetting.

Volume: 20, Issue: 2, Pages: 2150027
Published: Apr 23, 2021
Abstract
Concept drift detection algorithms have historically been faithful to the aged architecture of forcefully resetting the base classifiers for each detected drift. This approach prevents underlying classifiers becoming outdated as the distribution of a data stream shifts from one concept to another. In situations where both concept drift and temporal dependence are present within a data stream, forced resetting can cause complications in...
Paper Details
Title
Burst detection-based selective classifier resetting.
Published Date
Apr 23, 2021
Volume
20
Issue
2
Pages
2150027
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