NP-hard Problems of Learning From Examples

被引：14
|
作者：
Chen, Bin
Quan, Guangri
机构：
来源：
FIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 2, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/FSKD.2008.406
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
As designing practical algorithms of learning from examples, one has to deal with some optimization problems. The major optimization problems are: the smallest feature subset selection, the smallest decision tree induction, and the smallest k-DNF induction. In this paper, we show that all these optimization problems listed as above are NP-hard, and we present new greedy algorithms for solving these problems.
引用
收藏
页码：182 / 186
页数：5
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