A Classification and Novel Class Detection Algorithm for Concept Drift Data Stream Based on the Cohesiveness and Separation Index of Mahalanobis Distance
Joint Authors
Li, Xiangjun
Zhou, Yong
Jin, Ziyan
Yu, Peng
Zhou, Shun
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-03-19
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
Data stream mining has become a research hotspot in data mining and has attracted the attention of many scholars.
However, the traditional data stream mining technology still has some problems to be solved in dealing with concept drift and concept evolution.
In order to alleviate the influence of concept drift and concept evolution on novel class detection and classification, this paper proposes a classification and novel class detection algorithm based on the cohesiveness and separation index of Mahalanobis distance.
Experimental results show that the algorithm can effectively mitigate the impact of concept drift on classification and novel class detection.
American Psychological Association (APA)
Li, Xiangjun& Zhou, Yong& Jin, Ziyan& Yu, Peng& Zhou, Shun. 2020. A Classification and Novel Class Detection Algorithm for Concept Drift Data Stream Based on the Cohesiveness and Separation Index of Mahalanobis Distance. Journal of Electrical and Computer Engineering،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1183893
Modern Language Association (MLA)
Li, Xiangjun…[et al.]. A Classification and Novel Class Detection Algorithm for Concept Drift Data Stream Based on the Cohesiveness and Separation Index of Mahalanobis Distance. Journal of Electrical and Computer Engineering No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1183893
American Medical Association (AMA)
Li, Xiangjun& Zhou, Yong& Jin, Ziyan& Yu, Peng& Zhou, Shun. A Classification and Novel Class Detection Algorithm for Concept Drift Data Stream Based on the Cohesiveness and Separation Index of Mahalanobis Distance. Journal of Electrical and Computer Engineering. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1183893
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1183893