Bat Algorithm Based Hybrid Filter-Wrapper Approach
Joint Authors
Taha, Ahmed Majid
Chen, Soong-Der
Mustapha, Aida
Source
Advances in Operations Research
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-08
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Information Technology and Computer Science
Abstract EN
This paper presents a new hybrid of Bat Algorithm (BA) based on Mutual Information (MI) and Naive Bayes called BAMI.
In BAMI, MI was used to identify promising features which could potentially accelerate the process of finding the best known solution.
The promising features were then used to replace several of the randomly selected features during the search initialization.
BAMI was tested over twelve datasets and compared against the standard Bat Algorithm guided by Naive Bayes (BANV).
The results showed that BAMI outperformed BANV in all datasets in terms of computational time.
The statistical test indicated that BAMI has significantly lower computational time than BANV in six out of twelve datasets, while maintaining the effectiveness.
The results also showed that BAMI performance was not affected by the number of features or samples in the dataset.
Finally, BAMI was able to find the best known solutions with limited number of iterations.
American Psychological Association (APA)
Taha, Ahmed Majid& Chen, Soong-Der& Mustapha, Aida. 2015. Bat Algorithm Based Hybrid Filter-Wrapper Approach. Advances in Operations Research،Vol. 2015, no. 2015, pp.1-5.
https://search.emarefa.net/detail/BIM-1053800
Modern Language Association (MLA)
Taha, Ahmed Majid…[et al.]. Bat Algorithm Based Hybrid Filter-Wrapper Approach. Advances in Operations Research No. 2015 (2015), pp.1-5.
https://search.emarefa.net/detail/BIM-1053800
American Medical Association (AMA)
Taha, Ahmed Majid& Chen, Soong-Der& Mustapha, Aida. Bat Algorithm Based Hybrid Filter-Wrapper Approach. Advances in Operations Research. 2015. Vol. 2015, no. 2015, pp.1-5.
https://search.emarefa.net/detail/BIM-1053800
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1053800