Stability Analysis of Hierarchical Clustering for High Degree Dimension Data with a Temporary Element Method

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  • WATANABE Hidefumi
    Graduate School of Bio-Applications and Systems Engineering, Tokyo University of Agriculture and Technology
  • ICHIMIYA Kazumasa
    Department of Computer and Information Science, Tokyo University of Agriculture and Technology
  • SAITO Takafumi
    Graduate School of Bio-Applications and Systems Engineering, Tokyo University of Agriculture and Technology
  • MIYAMURA Hiroko NAKAMURA
    Japan Atomic Energy Agency

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Other Title
  • 仮想要素追加法による高次元データの階層的クラスタリング安定性解析
  • カソウ ヨウソ ツイカホウ ニ ヨル コウジゲン データ ノ カイソウテキ クラスタリング アンテイセイ カイセキ

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Abstract

We propose two methods to apply calculation of the stability of hierarchical clustering results by adding a temporary element method (ATEM) to high dimensional data. Using ATEM, we can calculate the stability of hierarchical clustering without statistical processing. However, ATEM needs fast calculation algorithm of super volume of high dimensional geometry. In this paper, we propose a sampling method calculating stability of every dimension from specific dimension in case the clustering with Euclidean distance and centroid method. In addition, we propose an acceleration method with a lookup table of stability and its interpolation. Combining these two methods, we can calculate the stability of every dimension in practical time. As results of comparing with Ben-Hur method that is one of the representative methods, we can calculate stability more than the equal and between 1,000 and 100,000 times faster than Ben-Hur method.

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