Ensemble of decision rules for ordinal classification with monotonicity constraints
[ 1 ] Instytut Informatyki, Wydział Informatyki, Politechnika Poznańska | [ 2 ] Instytut Informatyki (II), Wydział Informatyki i Zarządzania, Politechnika Poznańska | [ P ] pracownik
2008
referat
angielski
EN Ordinal classification problems with monotonicity constraints (also referred to as multicriteria classification problems) often appear in real-life applications, however they are considered relatively less frequently in theoretical studies than regular classification problems. We introduce a rule induction algorithm based on forward stagewise additive modeling that is tailored for this type of problems. The algorithm monotonizes the dataset (excludes highly inconsistent objects) using Dominance-based Rough Set Approach and generates monotone rules. Experimental results indicate that taking into account the knowledge about order and monotonicity constraints in the classifier can improve the prediction accuracy.
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