Constructive induction: A preprocessor

Yuh-Jyh Hu*

*此作品的通信作者

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

摘要

Inductive algorithms rely strongly on their representational biases. Representational inadequacy can be mitigated by constructive induction. This paper introduces the notion of relative gain measure and describes a new constructive induction algorithm (GALA) which generates a small number of new attributes from existing nominal or real-valued attributes. Unlike most previous research on constructive induction, our techniques are designed for use in preprocessing data set for subsequent use by any standard selective learning algorithms. We present results which demonstrate the effectiveness of GALA on both artificial and real domains with respect to C4.5 and CN2.

原文English
主出版物標題Advances in Artificial Intelligence - 11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 1996, Proceedings
編輯Gordon McCalla
發行者Springer Verlag
頁面249-256
頁數8
ISBN(列印)3540612912, 9783540612919
DOIs
出版狀態Published - 1 一月 1996
事件11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 1996 - Toronto, Canada
持續時間: 21 五月 199624 五月 1996

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
1081
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Conference

Conference11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 1996
國家/地區Canada
城市Toronto
期間21/05/9624/05/96

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