Logical analysis of data with decomposable structures

Hirotaka Ono, Kazuhisa Makino, Toshihide Ibaraki

研究成果: ジャーナルへの寄稿会議記事査読

5 被引用数 (Scopus)

抄録

In such areas as knowledge discovery, data mining and logical analysis of data, methodologies to find relations among attributes are considered important. In this paper, given a data set (T,F) where T ⊆ {0,1}n denotes a set of positive examples and F⊆{0,1}n denotes a set of negative examples, we propose a method to identify decomposable structures among the attributes of the data. We first study computational complexity of the problem of finding decomposable Boolean extensions. Since the problem turns out to be intractable (i.e., NP-complete), we propose a heuristic algorithm in the second half of the paper. Our method searches a decomposable partition of the set of all attributes by using the error sizes of almost-fit decomposable extensions as a guiding measure, and then finds structural relations among the attributes in the obtained partition. Some results of numerical experiment on randomly generated data sets are also reported.

本文言語英語
ページ(範囲)977-995
ページ数19
ジャーナルTheoretical Computer Science
289
2
DOI
出版ステータス出版済み - 10月 30 2002
イベントComputing and Combinatorics (COCOON 2000) - Sydney, NSW, オーストラリア
継続期間: 7月 1 20007月 1 2000

!!!All Science Journal Classification (ASJC) codes

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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