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Identifying moving variance to make automatic clustering for normal data set

Barakbah, Ali Ridho and Arai, Kohei (2004) Identifying moving variance to make automatic clustering for normal data set. In: IECI Japan Workshop 2004 (IJW 2004), 22 May 2004, Musashi Institute of Technology, Tokyo.

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    Abstract

    This paper proposed new approach to make cluster construction automatically for normal data set. The proposed method for automatic cluster construction is based on identifying moving variance of cluster for each stage of cluster construction, then analyzing the pattern to find the global optimum. After that, this paper proposed a new formulation to stop the construction of the cluster where it is in the global optimum, as well as to avoid the local optima. Experiment results will perform the effectiveness of the proposed method in this paper.

    Item Type: Conference or Workshop Item (Paper)
    Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
    Depositing User: Dr. Ali Ridho Barakbah
    Date Deposited: 22 Mar 2015 12:18
    Last Modified: 22 Mar 2015 12:18
    URI: http://repo.pens.ac.id/id/eprint/2731

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