A Simple Fitness Function for Minimum Attribute Reduction
Joint Authors
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-08-03
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
The goal of minimal attribute reduction is to find the minimal subset R of the condition attribute set C such that R has the same classification quality as C .
This problem is well known to be NP-hard.
When only one minimal attribute reduction is required, it was transformed into a nonlinearly constrained combinatorial optimization problem over a Boolean space and some heuristic search approaches were used.
In this case, the fitness function is one of the keys of this problem.
It required that the fitness function must satisfy the equivalence between the optimal solution and the minimal attribute reduction.
Unfortunately, the existing fitness functions either do not meet the equivalence, or are too complicated.
In this paper, a simple and better fitness function based on positive domain was given.
Theoretical proof shows that the optimal solution is equivalent to minimal attribute reduction.
Experimental results show that the proposed fitness function is better than the existing fitness function for each algorithm in test.
American Psychological Association (APA)
Su, Yuebin& Guo, Jin& Li, Zejun. 2015. A Simple Fitness Function for Minimum Attribute Reduction. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1057783
Modern Language Association (MLA)
Su, Yuebin…[et al.]. A Simple Fitness Function for Minimum Attribute Reduction. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-6.
https://search.emarefa.net/detail/BIM-1057783
American Medical Association (AMA)
Su, Yuebin& Guo, Jin& Li, Zejun. A Simple Fitness Function for Minimum Attribute Reduction. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1057783
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057783