Online Active Learning with Drifted Data Streams Using Paired Ensemble Framework

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Summary

A new online paired ensemble active learning framework consisting of a stable classifier and a timely substituted dynamic classifier to react to different types of concept drifts is proposed.

Type
article
Published
2017-01-01
Cited by
1
References
22
Access
Open access

Keywords

Classifier (UML), Computer science, Data stream mining, Machine learning, Concept drift

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