An evolutionary algorithm for clustering data streams with a variable number of clusters

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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

class="label">•: An evolutionary algorithm for clustering data stream is proposed.
class="label">•: Our algorithm allows estimating k automatically from the data in an online fashion.
class="label">•: It monitors eventual degradation in the quality of the induced clusters.
class="label">•: Results show our algorithm correctly detects, and react to, changes in a data stream.
class="label">•: The proposed method is very competitive in terms of accuracy and time processing.

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