Opposition chaotic fitness mutation based adaptive inertia weight BPSO for feature selection in text clustering
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- 作者：Kusum Kumari Bharti ; kkusum.bharti@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Pramod Kumar Singh pksingh@iiitm.ac.in" class="auth_mail" title="E-mail the corresponding author
- 关键词：Text clustering ; Binary particle swarm optimization ; Mutation ; Chaotic map ; Opposition-based learning
- 刊名：Applied Soft Computing
- 出版年：2016
- 出版时间：June 2016
- 年：2016
- 卷：43
- 期：Complete
- 页码：20-34
- 全文大小：1363 K
文摘
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A feature selection method based on binary particle swarm optimization is presented.
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Fitness based adaptive inertia weight is integrated with the binary particle swarm optimization to dynamically control the exploration and exploitation of the particle in the search space.
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Opposition and mutation are integrated with the binary particle swarm optimization improve it's search capability.
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The performance of the clustering algorithm improves with the features selected by proposed method.