Induction of Ordinal Decision Trees

Cor Bioch and Viara Popova

ERIM Report Series Research in Management from Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam

Abstract: This paper focuses on the problem of monotone decision trees from the point of view of the multicriteria decision aid methodology (MCDA). By taking into account the preferences of the decision maker, an attempt is made to bring closer similar research within machine learning and MCDA. The paper addresses the question how to label the leaves of a tree in a way that guarantees the monotonicity of the resulting tree. Two approaches are proposed for that purpose - dynamic and static labeling which are also compared experimentally. The paper further considers the problem of splitting criteria in the con- text of monotone decision trees. Two criteria from the literature are com- pared experimentally - the entropy criterion and the number of con criterion - in an attempt to find out which one fits better the specifics of the monotone problems and which one better handles monotonicity noise.

Keywords: monotone decision trees; multicriteria decision aid; multicriteria sorting; noise; ordinal classication (search for similar items in EconPapers)
JEL-codes: C49 M M11 R4 (search for similar items in EconPapers)
Date: 2003-02-10
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Citations: View citations in EconPapers (1)

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