A Novel Metric Embedding Optimal Normalization Mechanism for Clustering of Series Data

  • Authors:

  • Shigeyuki Mitsui;Katsumi Sakata;Hiroya Nobori;Setsuko Komatsu

  • Affiliations:

  • -;-;-;-

  • Venue:
  • IEICE - Transactions on Information and Systems
  • Year:
  • 2008

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Abstract

Clustering is indispensable to obtain a general view of series data from a number of data such as gene expression profiles. We propose a novel metric for clustering. The proposed metric automatically normalizes data to minimize a logarithmic scale distance between the data series.