39 Pages Posted: 18 Feb 2003
Date Written: 23 2002 4,
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.
Keywords: monotone, monotonicity constraint, classification tree, decision tree, ordinal data
JEL Classification: M, M11, R4, C6
Suggested Citation: Suggested Citation
Potharst, Rob and Feelders, A. J., Classification Trees for Problems with Monotonicity Constraints (23 2002 4,). ERIM Report Series Reference No. ERS-2002-45-LIS. Available at SSRN: https://ssrn.com/abstract=370989