Inducing classification rules from highly-structured data with composition

被引：0

作者：

MacKinney-Romero, R ^{[1
]}

Giraud-Carrier, C

机构：

[1] Univ Autonoma Metropolitana, Dept Ingn Elect, Mexico City 09950, DF, Mexico

[2] ELCA Informat SA, Lausanne, Switzerland

来源：

MICAI 2004: ADVANCES IN ARTIFICIAL INTELLIGENCE | 2004年 / 2972卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper elaborates on two techniques, deconstruction and composition, to handle complex data in order to learn from it. We propose typed higher-order logic as a suitable representation formalism for domains with complex structured data. Both techniques derive naturally from such framework. A naive sequential covering algorithm which uses both techniques is applied on well known learning datasets (simple and structured) to test them with good results. A further experiment on the change of knowledge representation is presented to showcase the robustness of our approach.

引用

页码：262 / 271

页数：10

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