Attribute Value Selection Considering the Minimum Description Length Approach and Feature Granularity

Abstract. In this paper we introduce a new approach to automatic attribute and granularity selection for building optimum regression trees. The method is based on the minimum description length principle (MDL) and aspects of granular computing. The approach is verified by giving an example using a data set which is extracted and preprocessed from an operational information system of the Components Toolshop of Volkswagen AG. Key words: Minimum Description Length, Granular Computing, Regression Tree, Decision Support, Intelligent Decision Algorithm

• Type: Journal
• Year: 2010
• Where: IPMU
• Authors: Kemal Ince, Frank Klawonn
• Keywords: Granular Computing, Information Technology, IPMU 2010, Minimum Description Length, Regression Tree