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11

IPMU
2010
Springer

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

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

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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

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Added	28 Jan 2011
Updated	28 Jan 2011
Type	Journal
Year	2010
Where	IPMU
Authors	Kemal Ince, Frank Klawonn

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