Comparison of lazy classification algorithms based on deterministic and inhibitory decision rules

被引：0

作者：

Delimata, Pawel ^{[1
]}

Moshkov, Mikhail ^{[2
]}

Skowron, Andrzej ^{[3
]}

Suraj, Zbigniew ^{[1
]}

机构：

[1] Univ Rzeszow, Rejtana 16A, PL-35310 Rzeszow, Poland

[2] Silesian Univ, Inst Comp Sci, PL-40007 Sosnowiec, Poland

[3] Univ Warsaw, Inst Math, PL-02097 Warsaw, Poland

来源：

ROUGH SETS AND KNOWLEDGE TECHNOLOGY | 2008年 / 5009卷

关键词：

rough sets; decision tables; deterministic decision rules; inhibitory decision rules;

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：

In the paper, two lazy classification algorithms of polynomial time complexity are considered. These algorithms are based on deterministic and inhibitory decision rules, but the direct generation of rules is not required. Instead of this, for any new object the considered algorithms extract from a given decision table efficiently some information about the set of rules. Next, this information is used by a decision-making procedure. The reported results of experiments show that the algorithms based on inhibitory decision rules are often better than those based on deterministic decision rules.

引用

页码：55 / +

页数：3

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