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dc.contributor.authorVanschoren, Joaquin
dc.contributor.authorBlockeel, Hendrik
dc.contributor.authorPfahringer, Bernhard
dc.contributor.authorHolmes, Geoffrey
dc.date.accessioned2012-05-23T02:50:46Z
dc.date.available2012-05-23T02:50:46Z
dc.date.copyright2012-05-05
dc.date.issued2012
dc.identifier.citationVanschoren, J., Blockeel, H., Praringer, B. & Holmes, G. (2012). Experiment databases: A new way to share, organize and learn from experiments. Machine Learning, 87(2), 127-158.en_NZ
dc.identifier.urihttps://hdl.handle.net/10289/6355
dc.description.abstractThousands of machine learning research papers contain extensive experimental comparisons. However, the details of those experiments are often lost after publication, making it impossible to reuse these experiments in further research, or reproduce them to verify the claims made. In this paper, we present a collaboration framework designed to easily share machine learning experiments with the community, and automatically organize them in public databases. This enables immediate reuse of experiments for subsequent, possibly much broader investigation and offers faster and more thorough analysis based on a large set of varied results. We describe how we designed such an experiment database, currently holding over 650,000 classification experiments, and demonstrate its use by answering a wide range of interesting research questions and by verifying a number of recent studies.en_NZ
dc.language.isoen
dc.publisherSpringeren_NZ
dc.relation.ispartofMachine Learning
dc.relation.urihttp://www.springerlink.com/content/4g68843816w477v8/en_NZ
dc.subjectexperimental methodologyen_NZ
dc.subjectmachine learningen_NZ
dc.subjectdatabasesen_NZ
dc.subjectmeta-learningen_NZ
dc.titleExperiment databases: A new way to share, organize and learn from experimentsen_NZ
dc.typeJournal Articleen_NZ
dc.identifier.doi10.1007/s10994-011-5277-0en_NZ
dc.relation.isPartOfMachine Learningen_NZ
pubs.begin-page127en_NZ
pubs.editionMayen_NZ
pubs.elements-id37010
pubs.end-page158en_NZ
pubs.issue2en_NZ
pubs.volume87en_NZ
uow.identifier.article-no2en_NZ


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