文章基本信息

标题：Study Of Fault Prediction Using Quad Tree Based K-Means Algorithm And Quad Tree Based EM Algorithm
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作者：Swapna M. Patil ; R.V.Argiddi
期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2014
卷号：3
期号：11
页码：9193-9196
出版社：IJECS
摘要：The paper intends to do a comparative study of the two clustering algorithms, namely K-Means and EM. Quad treeis used as a common algorithm to initialize both the clustering algorithms. The dataset is then clustered and classified separatelyby K-Means and EM algorithms. The motive of this paper is to prove the effectiveness of EM over K-Means. Classification andclustering of the dataset done via EM is seen to have lower faults as compared to clustering and classification done via K-Meansalgorithm
关键词：Quad Tree; K-Means clustering; Expectation Maximization Algorithm; Iris Dataset; Clustering; Classification; Hyper-Quad tree