MDL基準による判別木の生成

• 鈴木 秀男

  東京工業大学経営システム工学科

• 圓川 隆夫

  東京工業大学経営システム工学科

書誌事項

タイトル別名

• Generating Classification Trees Based on Minimum Description Length Criterion

抄録

This paper proposes an inference algorithm for classification trees based on MDL, the Minimum Description Length Criterion. MDL is a well known model selection criterion which stipulates that one should select a model so as to minimize the total number of bits to encode information necessary to reproduce the original data given as input, including the description of the model and the parameters. First, an exact expression of the description length of classification trees with a certain encoding scheme is given. Then an efficient algorithm to generate classification treesis proposed, in which trees are produced in a top-down manner by reducing the coding length by replacements of a terminal node with a decision node. Finally, simulation experiments are described which show that our algorithm based on MDL outperforms that using another related model selection criterion called AIC. In particular, the classification trees obtained using MDL were much more consistent with the true model.

収録刊行物

• 人工知能

  人工知能 10 (4), 572-579, 1995-07-01

  一般社団法人 人工知能学会

キーワード

• classification trees
• MDL
• algorithm based on the encoding length
• true sizes of trees

詳細情報

• CRID: 1390567172578762112
• NII論文ID: 110002806743
• NII書誌ID: AN10067140
• DOI: 10.11517/jjsai.10.4_572
• ISSN: 24358614
• ISSN: 21882266
• 本文言語コード: ja
• データソース種別:
  • JaLC
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可