An Ant Colony Optimization Based Feature Selection for Data Classification
Rajesh Dwivedi1, Rahul Kumar2, Ebenezer Jangam3, Vishnu Kumar4
1Rajesh Dwivedi, Department of Computer Science and Engineering, Vignan Foundation For Science Technology and Research, Guntur (A.P), India.
2Rahul Kumar, Department of Computer Science and Engineering, Vignan Foundation For Science Technology and Research, Guntur (A.P), India.
3Ebenezer Jangam, Department of Computer Science and Engineering, Vignan Foundation For Science Technology and Research, Guntur (A.P), India.
4Vishnu Kumar, Department of Computer Science and Engineering, Vignan Foundation For Science Technology and Research, Guntur (A.P), India.
Manuscript received on 12 February 2019 | Revised Manuscript received on 02 March 2019 | Manuscript Published on 08 June 2019 | PP: 35-40 | Volume-7 Issue-5S4, February 2019 | Retrieval Number: E10070275S419/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Feature selection is important process in the task of classification and clustering when the large number of feature gets extracted. In feature selection for n number of feature there are 2n feature subsets means every feature have two possibilities first possible is that particular feature would be selected for classification and other is would not be selected for classification. So finding a relevant feature subset in appropriate time is a NP-Hard problem. To avoid this problem, the approximation algorithm is used that gives the near optimal solution are four types including filter, wrapper, embedded and hybrid techniques. Many of the swarm intelligent algorithms that simulate the social behaviour of living beings are used as feature selection algorithms. The proposed method using the one of the swarm intelligent algorithm for feature selection based on ant colony optimization. This algorithm is combined with the Support vector machine classifierfor selecting the more appropriate and useful features.
Keywords: Feature Selection, Ant Colony Optimization, Data Classification.
Scope of the Article: Classification