Development of a Data-Clustering Method Focusing on Simplicity of Cluster Structures and Its Application to Chemoinformatics

DOI Web Site 6 References
  • AMANO Kou
    Research and Service Division of Materials Data and Integrated Systems, National Institute for Materials Science, 1-1-1 Sengen, Tsukuba-shi, Ibaraki 305-0047, Japan
  • YAMANOUCHI Akihiro
    Faculty of Advanced Science and Technology, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto-shi, Kumamoto 860-8555, Japan
  • SUGIMOTO Manabu
    Faculty of Advanced Science and Technology, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto-shi, Kumamoto 860-8555, Japan
  • WADA Masamichi
    Graduate School of Library, Information and Media Studies, University of Tsukuba, 1-2 Kasuga, Tsukuba-shi, Ibaraki 305-8550, Japan

Bibliographic Information

Other Title
  • クラスターの単純さに注目したデータ•クラスタリングの高精度化とそのケモインフォマティクスへの応用
Published
2017
Resource Type
journal article
DOI
  • 10.2477/jccj.2017-0062
Publisher
Society of Computer Chemistry, Japan

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Description

<p>A cluster validity index (CVI) called "simplicity index" (SI) is newly proposed to enhance the accuracy of data clustering in machine learning. This index is derived to emphasize the importance of simplicity in cluster structures. The characteristics ofSI and its advantages over the known methods in the literature are discussed. SI is applied to classification of nucleotide sequences of nitrogen-fixing genes.</p>

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