Quasi-optimality under pseudo f statistic in clustering data

  • Authors

    • Teruhisa Hochin
    • Yoshihiro Hayashi
    • Hiroki Nomiya
    • Morshed U. Chowdhury
    2018-05-16
    https://doi.org/10.14419/ijet.v7i2.28.13205
  • Clustering, Difference, Pseudo F Statistic, Quasi-Optimum, Relative Difference.

  • Pseudo F statistic is often used in deciding the number of clusters. A set of clusters having the largest pseudo F value is selected as the op-timum set of clusters. This paper proposes the quasi-optimum set of clusters, whose pseudo F value is larger than those of other sets of clusters, whose numbers are around the number of clusters in the quasi-optimum set. The before and behind (BB) difference of pseudo F values is proposed to find the number of clusters in the quasi-optimum set. The relative BB difference of pseudo F values, which is the ratio of the BB difference of pseudo F values to the pseudo F value itself, is also proposed to find it when the pseudo F value severely varies. This paper shows some examples to demonstrate that the BB differences of pseudo F values and the relative ones work well in finding qua-si-optimum sets of clusters.

     

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  • How to Cite

    Hochin, T., Hayashi, Y., Nomiya, H., & U. Chowdhury, M. (2018). Quasi-optimality under pseudo f statistic in clustering data. International Journal of Engineering & Technology, 7(2.28), 320-324. https://doi.org/10.14419/ijet.v7i2.28.13205