An evolutionary algorithm for clustering data streams with a variable number of clusters
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- 作者：Jonathan de Andrade Silva ; 1 ; a ; jonathan.andrade@ufms.br" class="auth_mail" title="E-mail the corresponding author ; Eduardo Raul Hruschka2 ; b ; erh@icmc.usp.br" class="auth_mail" title="E-mail the corresponding author ; Joã ; o Gama3 ; c ; jgama@fep.up.pt" class="auth_mail" title="E-mail the corresponding author
- 关键词：Evolutionary algorithms ; Clustering ; Data streams ; Concept drift
- 刊名：Expert Systems with Applications
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：67
- 期：Complete
- 页码：228-238
- 全文大小：1437 K
文摘
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An evolutionary algorithm for clustering data stream is proposed.
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Our algorithm allows estimating k automatically from the data in an online fashion.
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It monitors eventual degradation in the quality of the induced clusters.
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Results show our algorithm correctly detects, and react to, changes in a data stream.
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The proposed method is very competitive in terms of accuracy and time processing.