How good is the Electricity benchmark for evaluating concept drift adaptation

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How good is the Electricity benchmark for evaluating concept drift adaptation

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arxiv 1301.3524 v1 pith:QD4NVSVZ submitted 2013-01-15 cs.LG

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classification cs.LG

keywords adaptationaccuracyadaptivealarmsautocorrelatedbenchmarkboostcannot

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In this correspondence, we will point out a problem with testing adaptive classifiers on autocorrelated data. In such a case random change alarms may boost the accuracy figures. Hence, we cannot be sure if the adaptation is working well.

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A Scalable Approach to Covariate and Concept Drift Management via Adaptive Data Segmentation
cs.LG 2024-11 conditional novelty 4.0 of 10

A drift-management framework that selects training segments by concept-drift scores and ranks batches inside them by random-forest leaf proximity to test data, yielding small accuracy gains over Quilt on most benchmar...

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