Affiliation:
1. Tokyo Institute of Technology, Japan
Abstract
This chapter introduces a discovery method of attractive rules from the tabular structured data. The data is a set of examples composed of attributes and their attribute values. The method is included in the research field discovering frequent patterns from transactions composed of items. Here, the transaction and the item are a receipt and a sales item in the case of the retail business. The method focuses on relationships between the attributes and the attribute values in order to efficiently discover patterns based on their frequencies from the tabular structured data. Also, the method needs to deal with missing values. This is because parts of attribute values are missing due to the problems of data collection and data storage. Thus, this chapter introduces a method dealing with the missing values. The method defines two evaluation criteria related to the patterns and introduces a method that discovers the patterns based on the two-stepwise evaluation method. In addition, this chapter introduces evaluation criteria of the attractive rules in order to discover the rules from the patterns.
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