Decision tree induction from numeric data stream

Satoru Nishimura, Masahiro Terabe, Kazuo Hashimoto

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Hoeffding Tree Algorithm is known as a method to induce decision trees from a data stream. Treatment of numeric attribute on Hoeffding Tree Algorithm has been discussed for stationary input. It has not yet investigated, however, for non-stationary input where the effect of concept drift is apparent. This paper identifies three major approaches to handle numeric values, Exhaustive Method, Gaussian Approximation, and Discretizaion Method, and through experiment shows the best suited modeling of numeric attributes for Hoeffding Tree Algorithm. This paper also experimentaly compares the performance of two known methods for concept drift detection, Hoeffding Bound Based Method and Accuracy Based Method.

本文言語English
ホスト出版物のタイトルAI 2008
ホスト出版物のサブタイトルAdvances in Artificial Intelligence - 21st Australasian Joint Conference on Artificial Intelligence, Proceedings
ページ311-317
ページ数7
DOI
出版ステータスPublished - 2008 12 1
外部発表はい
イベント21st Australasian Joint Conference on Artificial Intelligence, AI 2008 - Auckland, New Zealand
継続期間: 2008 12 12008 12 5

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
5360 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference21st Australasian Joint Conference on Artificial Intelligence, AI 2008
国/地域New Zealand
CityAuckland
Period08/12/108/12/5

ASJC Scopus subject areas

  • 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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