Rules and Apriori Algorithm in Non-deterministic Information Systems
Rules and Apriori Algorithm in Non-deterministic Information Systems
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DOI：
10.1007/978-3-540-89876-4_18
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发表时间：
2008-01-01
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影响因子：
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通讯作者：
Nakata, Michinori
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文献类型：
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作者：
Sakai, Hiroshi;Ishibashi, Ryuji;Nakata, Michinori
针对确定性信息系统(D[SS)中基于粗糙集的规则生成问题，提出了一种非确定性信息系统(NISS)规则生成框架。我们以前关于NISS的工作处理了某些规则、最小某些规则和可能的规则。这些规则的特点是一致性的概念。本文通过NISS中的标准支持度和准确性将可能的规则与规则相关联。基于NISS中信息的不完备性，可以定义新的标准，即最小支持度、最大支持度、最小准确度和最大准确度。在此基础上，提出了两种规则生成策略。第一种策略是下近似策略，它定义了最坏情况下的规则生成。第二种策略是上近似策略，它定义了在最佳条件下的规则生成。为了实现这些策略，我们将DISS中的APRIPORI算法扩展到NISS中的APRIPORI算法。实现了一个原型系统，并将该系统应用于一些不完全信息的数据集。
This paper presents a framework of rule generation in Non-deterministic Information Systems (NISs), which follows rough sets based rule generation in Deterministic Information Systems (D[Ss). Our previous work about NISs coped with certain rules, minimal certain rules and possible rules. These rules are characterized by the concept of consistency. This paper relates possible rules to rules by the criteria support and accuracy in NISs. On the basis of the information incompleteness in NISs; it is possible to define new criteria, i.e., minimum support, maximum support, minimum accuracy and maximum accuracy. Then, two strategies of rule generation are proposed based on these criteria. The first strategy is Lower Approximation strategy, which defines rule generation under the worst condition. The second strategy is Upper Approximation strategy, which defines rule generation under the best condition. To implement these strategies, we extend Apriori algorithm in DISs to Apriori algorithm in NISs. A prototype system is implemented, and this system is applied to some data sets with incomplete information.