Classification Trees for Problems with Monotonicity Constraints
Erasmus University Rotterdam - Department of Computer Science; Erasmus Research Institute of Management (ERIM)
A. J. Feelders
University of Utrecht
23 2002 4,
ERIM Report Series Reference No. ERS-2002-45-LIS
For classification problems with ordinal attributes very often theclass attribute should increase with each or some of theexplaining attributes. These are called classification problemswith monotonicity constraints. Classical decision tree algorithmssuch as CART or C4.5 generally do not produce monotone trees, evenif the dataset is completely monotone. This paper surveys themethods that have so far been proposed for generating decisiontrees that satisfy monotonicity constraints. A distinction is madebetween methods that work only for monotone datasets and methodsthat work for monotone and non-monotone datasets alike.
Number of Pages in PDF File: 39
Keywords: monotone, monotonicity constraint, classification tree, decision tree, ordinal data
JEL Classification: M, M11, R4, C6working papers series
Date posted: February 18, 2003
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