Show simple item record  

dc.contributor.authorPfahringer, Bernhard
dc.contributor.authorHolmes, Geoffrey
dc.contributor.authorKirkby, Richard Brendon
dc.coverage.spatialConference held at Gold Coast, Australiaen_NZ
dc.date.accessioned2009-01-09T03:42:59Z
dc.date.available2009-01-09T03:42:59Z
dc.date.issued2007
dc.identifier.citationPfahringer, B., Holmes, G. & Kirkby, R. (2007). New Options for Hoeffding Trees. In M.A. Orgun & J. Thornton(Eds), Proceedings of 20th Australian Joint Conference on Artificial Intelligence, Gold Coast, Australia, December 2-6, 2007. Berlin, Germany: Springer.en
dc.identifier.urihttps://hdl.handle.net/10289/1761
dc.description.abstractHoeffding trees are state-of-the-art for processing high-speed data streams. Their ingenuity stems from updating sufficient statistics, only addressing growth when decisions can be made that are guaranteed to be almost identical to those that would be made by conventional batch learning methods. Despite this guarantee, decisions are still subject to limited lookahead and stability issues. In this paper we explore Hoeffding Option Trees, a regular Hoeffding tree containing additional option nodes that allow several tests to be applied, leading to multiple Hoeffding trees as separate paths. We show how to control tree growth in order to generate a mixture of paths, and empirically determine a reasonable number of paths. We then empirically evaluate a spectrum of Hoeffding tree variations: single trees, option trees and bagged trees. Finally, we investigate pruning. We show that on some datasets a pruned option tree can be smaller and more accurate than a single tree.en
dc.language.isoen
dc.publisherSpringeren
dc.relation.urihttp://www.springerlink.com/content/r5287p50x2137n27/en
dc.sourceAI 2007en_NZ
dc.subjectcomputer scienceen
dc.subjectHoeffding treeen
dc.subjectMachine learning
dc.titleNew Options for Hoeffding Treesen
dc.typeConference Contributionen
dc.identifier.doi10.1007/978-3-540-76928-6_11en
dc.relation.isPartOfProc 20th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligenceen_NZ
pubs.begin-page90en_NZ
pubs.elements-id17446
pubs.end-page99en_NZ
pubs.finish-date2007-12-06en_NZ
pubs.place-of-publicationGermanyen_NZ
pubs.start-date2007-12-02en_NZ
pubs.volumeLNCS 4830en_NZ


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record