文章基本信息

标题：MO & ESC - The New Approach in Impurity Centroids
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作者：G.Rajasekar ; R.Vijayakumar ; T.Aravind 等
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2014
卷号：2
期号：3
出版社：S&S Publications
摘要：Clustering is used to determine the intrinsic grouping in a set of unlabeled data. Subspace clustering is one type of clustering model that solves many normal clustering problems. The both novel subspace clustering algorithms known as fixed and optimal centroids are allows getting more profitable objects in database. But this also provides information with impurity data. So we propo sed a new approach called Multi Objective and Evolutionary Subspace Clustering (MO&ESC) that provides statistic of the dimensions and the impurity measure within each cluster. This technique is used to provide Centroid - based Actionable 3D Subspace clusters and also returns the information based on impurity dimensional data value.
关键词：Clustering; Data mining; Centroid; Multi Objecti ve and E ; volutionary Subspace Clustering