ROUGH SETS - PROBABILISTIC VERSUS DETERMINISTIC APPROACH

被引：316

作者：

PAWLAK, Z ^{[1
]}

WONG, SKM ^{[1
]}

ZIARKO, W ^{[1
]}

机构：

[1] UNIV REGINA,DEPT COMP SCI,REGINA S4S 0A2,SASKATCHEWAN,CANADA

来源：

INTERNATIONAL JOURNAL OF MAN-MACHINE STUDIES | 1988年 / 29卷 / 01期

关键词：

Decision Theory and Analysis - Probability - Systems Science and Cybernetics--Learning Systems;

D O I：

10.1016/S0020-7373(88)80032-4

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

A method for simplifying a given knowledge representation system is presented. The probabilistic model is also introduced. The similarities between the probabilistic and deterministic models are highlighted. It is demonstrated that all basic concepts of the deterministic theory have their equivalence in the probabilistic approach. The paper focuses on the differences between the two models in the context of their utility for inducing decision rules from a set of examples. Some known and potential applications of both models in medical diagnosis, engineering control and machine learning systems are discussed.

引用

页码：81 / 95

页数：15