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Optimization of attribute selection model using bio-inspired algorithms


Basir, Mohammad Aizat and Yusof, Yuhanis and Hussin, Mohamed Saifullah (2019) Optimization of attribute selection model using bio-inspired algorithms. Journal of ICT, 18 (1). pp. 35-55. ISSN 1675-414X

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Abstract

Attribute selection which is also known as feature selection is an essential process that is relevant to predictive analysis.To date, various feature selection algorithms have been introduced, nevertheless they all work independently. Hence, reducing the consistency of the accuracy rate. The aim of this paper is to investigate the use of bio-inspired search algorithms in producing optimal attribute set. This is achieved in two stages; 1) create attribute selection models by combining search method and feature selection algorithms, and 2) determine an optimized attribute set by employing bio-inspired algorithms.Classification performance of the produced attribute set is analyzed based on accuracy and number of selected attributes. Experimental results conducted on six (6) public real datasets reveal that the feature selection model with the implementation of bio-inspired search algorithm consistently performs good classification (i.e higher accuracy with fewer numbers of attributes) on the selected data set. Such a finding indicates that bio-inspired algorithms can contribute in identifying the few most important features to be used in data mining model construction.

Item Type: Article
Uncontrolled Keywords: Feature selection, bio-inspired algorithms, data classification, data mining.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: School of Computing
Depositing User: Mrs. Norazmilah Yaakub
Date Deposited: 12 Feb 2019 07:45
Last Modified: 12 Feb 2019 07:45
URI: http://repo.uum.edu.my/id/eprint/25567

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