Front Inner Page - Volume 3 No.6 December 2016

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  • Title

    :

    A Survey On Data Partitioning And Cluster Ensemble Techniques

    Authors

    :

    D.Dennis Ebenezer1, M. Suganya2

    Keywords

    :

    Data Clusters, Data Partitioning Techniques, Cluster Ensembles and Similarity Measures.

    Issue Date

    :

    December 2016

    Abstract

    :

    Data mining methods are used to discover the knowledge from the databases. Association rule mining, classification and clustering techniques are applied for the knowledge discovery process. The data clustering method is also called as data partitioning method. The similar data values are partitioned under the clustering process. The data similarity is measured with distance or similarity measures. The data partitioning process is carried out with the partition and hierarchical models. High dimensional data clustering is a complex task. The cluster ensemble approaches are adapted to reduce the complexity level of high dimensional data clustering process. K-means, K- Medoids and Partion around Medoids (PAM) clustering algorithms are applied for the data clustering process. The survey is conducted to analyze the various techniques and cluster ensemble methods. Cluster results evaluation methods are also analyzed in the survey.

    Page(s)

    :

    1-6

    ISSN

    :

    2347- 4734

    Source

    :

    Vol. 3, No.6, December 2016

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