MACHINE LEARNING IN ARTIFICIAL-INTELLIGENCE

被引:6
|
作者
BRATKO, I
机构
[1] UNIV LJUBLJANA,FAC ELECTR ENGN & COMP SCI,LJUBLJANA,SLOVENIA
[2] J STEFAN INST,LJUBLJANA,SLOVENIA
来源
ARTIFICIAL INTELLIGENCE IN ENGINEERING | 1993年 / 8卷 / 03期
关键词
D O I
10.1016/0954-1810(93)90002-W
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Among several forms of learning, learning concepts from examples is the most common and best understood. In this paper some approaches to learning concepts from examples are reviewed. In particular those approaches that are currently most important with respect to practical applications (learning decision trees and if-then rules), or likely to become very important in the near future (Inductive Logic Programming as a form of relational learning) are discussed.
引用
收藏
页码:159 / 164
页数:6
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