Efficient Ensemble Classification for Multi-Label Data Streams with Concept Drift

Efficient Ensemble Classification for Multi-Label Data Streams with Concept Drift

Most existing multi-label data streams classification methods focus on extending single-label streams classification approaches to multi-label cases, without considering the special characteristics of multi-label stream data, such as label dependency, concept drift, and recurrent concepts. Motivated...

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Bibliographic Details
Main Authors: Yange Sun, Han Shao, Shasha Wang
Format: Article
Language:English
Published: MDPI AG 2019-04-01
Series:Information
Subjects:
data streams
multi-label
concept drift
ensemble classification
label dependency
Online Access:https://www.mdpi.com/2078-2489/10/5/158

Internet

https://www.mdpi.com/2078-2489/10/5/158

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