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ROUGH SET-BASED APPROACH TO RULE GENERATION AND RULE INDUCTION

机译:基于粗糙集的规则生成和规则诱导方法

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During the last decade, databases have been growing rapidly in size and number as a result of rapid advances in database capacity and management techniques. This expansive growth in data and databases has caused a pressing need for the development of more powerful techniques to convert the vast pool of data into valuable information. For the purpose of strategic and decision-making, many companies and researchers have recognized mining useful information and knowledge from large databases as a key research topic and as an opportunity for major revenues and improving competitiveness. In this paper, we will explore a new rule generation algorithm (based on rough sets theory) that can generate a minimal set of rule reducts, and a rule generation and rule induction program (RGRIP) which can efficiently induce decision rules from conflicting information systems. All the methods will also be illustrated with numerical examples.
机译:在过去的十年中,由于数据库容量和管理技术的快速发展,数据库的规模和数量都在迅速增长。数据和数据库的迅速增长导致迫切需要开发更强大的技术,以将大量数据转换为有价值的信息。出于战略和决策制定的目的,许多公司和研究人员已经认识到从大型数据库中挖掘有用的信息和知识是一个关键的研究主题,也是获得主要收入和提高竞争力的机会。在本文中,我们将探索一种新的规则生成算法(基于粗糙集理论),该算法可以生成最小的规则约简集,以及规则生成和规则归纳程序(RGRIP),可以有效地从冲突的信息系统中诱导决策规则。所有方法还将通过数值示例进行说明。

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