PatHT : an efficient method of classification over evolving data streams
Joint Authors
Source
The International Arab Journal of Information Technology
Issue
Vol. 16, Issue 6 (30 Nov. 2019), pp.1098-1105, 8 p.
Publisher
Publication Date
2019-11-30
Country of Publication
Jordan
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
Some existing classifications need frequent update to adapt to the change of concept in data streams.
To solve this problem, an adaptive method Pattern-based Hoeffding Tree (PatHT) is proposed to process evolving data streams.
A key technology of a training classification decision tree is to improve the efficiency of choosing an optimal splitting attribute.
Therefore, frequent patterns are used.
Algorithm PatHT discovers constraint-based closed frequent patterns incremental updated.
It builds an adaptive and incremental updated tree based on the frequent pattern set.
It uses sliding window to avoid concept drift in mining patterns and uses concept drift detector to deal with concept change problem in procedure of training examples.
We tested the performance of PatHT against some known algorithms using real data streams and synthetic data streams with different widths of concept change.
Our approach outperforms traditional classification models and it is proved by the experimental results.
American Psychological Association (APA)
Han, Meng& Ding, Jian& Li, Juan. 2019. PatHT : an efficient method of classification over evolving data streams. The International Arab Journal of Information Technology،Vol. 16, no. 6, pp.1098-1105.
https://search.emarefa.net/detail/BIM-915121
Modern Language Association (MLA)
Han, Meng…[et al.]. PatHT : an efficient method of classification over evolving data streams. The International Arab Journal of Information Technology Vol. 16, no. 6 (Nov. 2019), pp.1098-1105.
https://search.emarefa.net/detail/BIM-915121
American Medical Association (AMA)
Han, Meng& Ding, Jian& Li, Juan. PatHT : an efficient method of classification over evolving data streams. The International Arab Journal of Information Technology. 2019. Vol. 16, no. 6, pp.1098-1105.
https://search.emarefa.net/detail/BIM-915121
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 1104-1105
Record ID
BIM-915121