2値変量に基づく教師無し分類における類似係数の選択

• 石田 実

  株式会社アークエンジン

• 西尾 チヅル

  筑波大学ビジネス科学研究科

• 椿 広計

  統計数理研究所

書誌事項

タイトル別名

• Choosing a Similarity Coefficient for Classification by Binary Variables
• 2チ ヘンリョウ ニ モトズク キョウシ ナシ ブンルイ ニ オケル ルイジ ケイスウ ノ センタク

抄録

Pairwise similarity coefficients are popular measure for binary variables. Many different measures of similarity have been proposed in the literature. Then we are interested in which one is the most effective for classifications. We focus on the fact that almost all measures of similarity are composed of interactions and main effects, and conjecture that the most useful similarity is an interaction because main effect don't play a role of classifications but totally order. All combinations of sixteen similarities coefficients and five clustering method were tested with music CD POS data. The cluster validation were assessed by interpretable, uniform, reproducible, external and internal criteria. As a result, the similarity coefficient which is more correlative with an interaction turns out more useful for classifications. That is, the best similarity is an interaction.

収録刊行物

• 行動計量学

  行動計量学 38 (1), 65-81, 2011

  日本行動計量学会

キーワード

• 類似係数
• クラスターバリデーション
• ジョイントセグメンテーション

詳細情報

• CRID: 1390001205178102784
• NII論文ID: 10029133698
• NII書誌ID: AN0008437X
• DOI: 10.2333/jbhmk.38.65
• ISSN: 18804705
• ISSN: 03855481
• NDL書誌ID: 11186718
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I11186718
• 本文言語コード: ja
• データソース種別:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• 抄録ライセンスフラグ: 使用不可