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IPMU
2010
Springer

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

9 years 8 months ago
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
Kemal Ince, Frank Klawonn
Added 28 Jan 2011
Updated 28 Jan 2011
Type Journal
Year 2010
Where IPMU
Authors Kemal Ince, Frank Klawonn
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