Time series data analysis by rough set and merging method of decision rule

Abstract

Rough set theory was proposed by Z. Pawlak in 1982. This theory can mine knowledge through a decision rule from a database, a web base, a set and so on. The decision rule is used for data analysis as well. And we can reason for an unknown object using the decision rule. However, there are cases where too many decision rules are found. It is difficult to acquire knowledge from too many rules. In this paper, we propose a method to reduce the number of rules by merging decision rules. It is difficult to acquire knowledge from many rules. It is also difficult to find knowledge from rules with a large number of condition attributes. We propose a method to reduce condition attributes. We think that reducing the number of rules by reducing the condition attribute. We analyze time series data using this proposed method. Acquire knowledge for prediction from time series data using decision rule. TOPIX is used as time series data. Analyze TOPIX data and acquire knowledge for prediction.