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| Titel: |
Learning Rule Ensembles for Ordinal Classification with Monotonicity Constraints |
| Auteur: |
Dembczyński, Krzysztof Kotłowski., Wojciech Słowiński, Roman |
| Verschenen in: |
Fundamenta informaticae |
| Paginering: | Jaargang 94 (2009) nr. 2 pagina's 163-178 |
| Jaar: |
2009-10-27 |
| Inhoud: |
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 the statistical learning approach that is tailored for this type of problems. The algorithm first monotonizes the dataset (excludes strongly inconsistent objects), using Stochastic Dominance-based Rough Set Approach, and then uses forward stagewise additive modeling framework for generating a monotone rule ensemble. Experimental results indicate that taking into account knowledge about order andmonotonicity constraints in the classifier can improve the prediction accuracy. |
| Uitgever: |
IOS Press |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 8 van 11 gevonden artikelen
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