Výsledky vyhledávání - "Punithavalli, M."

Mining Time Series data has a tremendous growth of interest in today's world. To provide an indication various implementations are studied and summarized to identify the different problems in existing applications. Clustering time series is a trouble

Externí odkaz: http://arxiv.org/abs/1005.4270

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Document Clustering using Sequential Information Bottleneck Method

Autor: Gayathri, P. J., Punitha, S. C., Punithavalli, M.

Publikováno v: IJCSIS, Vol. 7 No. 3, March 2010, 305-312

This paper illustrates the Principal Direction Divisive Partitioning (PDDP) algorithm and describes its drawbacks and introduces a combinatorial framework of the Principal Direction Divisive Partitioning (PDDP) algorithm, then describes the simplifie

Externí odkaz: http://arxiv.org/abs/1004.1796

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An Analytical Study on Behavior of Clusters Using K Means, EM and K* Means Algorithm

Autor: Nathiya, G., Punitha, S. C., Punithavalli, M.

Publikováno v: IJCSIS, Vol. 7 No. 3, March 2010, 185-190

Clustering is an unsupervised learning method that constitutes a cornerstone of an intelligent data analysis process. It is used for the exploration of inter-relationships among a collection of patterns, by organizing them into homogeneous clusters.

Externí odkaz: http://arxiv.org/abs/1004.1743

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