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dc.contributor.authorHolmes, Geoffrey
dc.contributor.authorPfahringer, Bernhard
dc.contributor.authorKirkby, Richard Brendon
dc.contributor.authorFrank, Eibe
dc.contributor.authorHall, Mark A.
dc.date.accessioned2008-10-10T03:47:03Z
dc.date.available2008-10-10T03:47:03Z
dc.date.issued2002-03
dc.identifier.citationHolmes, G., Pfahringer, B., Kirkby, R., Frank, E. & Hall, M. (2002). A logic boosting approach to inducing multiclass alternating decision trees. (Working paper 01/02). Hamilton, New Zealand: University of Waikato, Department of Computer Science.en_US
dc.identifier.issn1170-487X
dc.identifier.urihttps://hdl.handle.net/10289/1012
dc.description.abstractThe alternating decision tree (ADTree) is a successful classification technique that combine decision trees with the predictive accuracy of boosting into a ser to interpretable classification rules. The original formulation of the tree induction algorithm restricted attention to binary classification problems. This paper empirically evaluates several methods for extending the algorithm to the multiclass case by splitting the problem into several two-class LogitBoost procedure to induce alternating decision trees directly. Experimental results confirm that this procedure is comparable with methods that are based on the original ADTree formulation in accuracy, while inducing much smaller trees.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherUniversity of Waikato, Department of Computer Scienceen_US
dc.relation.ispartofseriesComputer Science Working Papers
dc.subjectcomputer scienceen_US
dc.titleA logic boosting approach to inducing multiclass alternating decision treesen_US
dc.typeWorking Paperen_US
uow.relation.series01/02
pubs.elements-id52143
pubs.place-of-publicationHamilton, New Zealanden_NZ


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