Diversity-driven widening

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IVANOVA, Violeta, Michael BERTHOLD, 2013. Diversity-driven widening. In: TUCKER, Allan, ed., Frank HÖPPNER, ed., Arno SIEBES, ed., Stephen SWIFT, ed.. Advances in Intelligent Data Analysis XII. Berlin, Heidelberg:Springer Berlin Heidelberg, pp. 223-236. ISBN 978-3-642-41397-1

@inproceedings{Ivanova2013Diver-26488, title={Diversity-driven widening}, year={2013}, doi={10.1007/978-3-642-41398-8_20}, number={8207}, isbn={978-3-642-41397-1}, address={Berlin, Heidelberg}, publisher={Springer Berlin Heidelberg}, series={Lecture Notes in Computer Science}, booktitle={Advances in Intelligent Data Analysis XII}, pages={223--236}, editor={Tucker, Allan and Höppner, Frank and Siebes, Arno and Swift, Stephen}, author={Ivanova, Violeta and Berthold, Michael} }

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/26488"> <dc:creator>Berthold, Michael</dc:creator> <dc:language>eng</dc:language> <dcterms:title>Diversity-driven widening</dcterms:title> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2014-02-20T10:00:30Z</dc:date> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2014-02-20T10:00:30Z</dcterms:available> <dc:rights>deposit-license</dc:rights> <dc:creator>Ivanova, Violeta</dc:creator> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/26488"/> <dcterms:abstract xml:lang="eng">This paper follows our earlier publication, where we introduced the idea of tuned data mining which draws on parallel resources to improve model accuracy rather than the usual focus on speed-up. In this paper we present a more in-depth analysis of the concept of Widened Data Mining, which aims at reducing the impact of greedy heuristics by exploring more than just one suitable solution at each step. In particular we focus on how diversity considerations can substantially improve results. We again use the greedy algorithm for the set cover problem to demonstrate these effects in practice.</dcterms:abstract> <dcterms:issued>2013</dcterms:issued> <dcterms:rights rdf:resource="http://nbn-resolving.org/urn:nbn:de:bsz:352-20140905103605204-4002607-1"/> <dc:contributor>Berthold, Michael</dc:contributor> <dcterms:bibliographicCitation>Advances in intelligent data analysis XII: 12th international symposium ; proceedings / IDA 2013, London, UK, October 17 - 19, 2013 / Allan Tucker, Frank Höppner, Arno Siebes, Stephen Swift (eds.). - Heidelberg [u.a.] : Springer, 2013. - S. 223-236. - (Lecture notes in computer science ; 8207). - ISBN 978-3-642-41397-1</dcterms:bibliographicCitation> <dc:contributor>Ivanova, Violeta</dc:contributor> </rdf:Description> </rdf:RDF>

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