ble2:使用粗糙集从例子中学习贝叶斯规则

22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003 Pub Date : 2003-07-24 DOI:10.1109/NAFIPS.2003.1226779

Chien-Chung Chan, Santhosh Sengottiyan

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引用次数: 18

摘要

介绍了一种利用粗糙集从实例中学习贝叶斯规则的算法。诱导规则与Pawlak在研究粗糙集理论与贝叶斯定理之间的联系时所定义的支持、确定性、强度和覆盖因子的性质有关。介绍了LEM2和BLEM2两种学习算法的区别。讨论了如何利用归纳规则的特性来开发一个优化的推理引擎。

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BLEM2: learning Bayes' rules from examples using rough sets

This paper introduces an algorithm for learning Bayes' rules from examples using rough sets. Induced rules are associated with properties of support, certainty, strength, and coverage factors as defined by Pawlak in his study of connections between rough set theory and Bayes' theorem. Differences between the two learning algorithms LEM2 and BLEM2 are presented. An idea of how to develop an optimized inference engine by taking advantage of induced rule properties is discussed.

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22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003

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