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Mixture of metrics optimization for machine learning problems

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Mixture of metrics optimization for machine learning problems

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dc.contributor.author Wiercioch, Magdalena [SAP14022105] pl
dc.contributor.author Śmieja, Marek [SAP14005333] pl
dc.date.accessioned 2016-06-16T11:46:42Z
dc.date.available 2016-06-16T11:46:42Z
dc.date.issued 2015 pl
dc.identifier.issn 1732-3916 pl
dc.identifier.uri http://ruj.uj.edu.pl/xmlui/handle/item/28032
dc.language eng pl
dc.rights Dozwolony użytek utworów chronionych *
dc.rights.uri http://ruj.uj.edu.pl/4dspace/License/copyright/licencja_copyright.pdf *
dc.title Mixture of metrics optimization for machine learning problems pl
dc.type JournalArticle pl
dc.description.physical 83-92 pl
dc.abstract.en The selection of data representation and metric for a given data set is one of the most crucial problems in machine learning since it affects the results of classification and clustering methods. In this paper we investigate how to combine a various data representations and metrics into a single function which better reflects the relationships between data set elements than a single representation-metric pair. Our approach relies on optimizing a linear combination of selected distance measures with use of least square approximation. The application of our method for classification and clustering of chemical compounds seems to increase the accuracy of these methods. pl
dc.subject.en metric learning pl
dc.subject.en clustering pl
dc.subject.en classification pl
dc.subject.en chemical compound activity pl
dc.subject.en fingerprint pl
dc.description.volume 24 pl
dc.identifier.doi 10.4467/20838476SI.15.008.3030 pl
dc.identifier.eissn 2083-8476 pl
dc.title.journal Schedae Informaticae pl
dc.language.container eng pl
dc.affiliation Wydział Matematyki i Informatyki : Instytut Informatyki i Matematyki Komputerowej pl
dc.subtype Article pl
dc.rights.original OTHER; otwarte czasopismo; ostateczna wersja wydawcy; w momencie opublikowania; 0 pl
dc.identifier.project ROD UJ / P pl
.pointsMNiSW [2015 B]: 11


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