Outlier Detection Using the Multiobjective Genetic Algorithm

Uproszczony widok
dc.contributor.authorDuraj, Agnieszka
dc.contributor.authorChomątek, Łukasz
dc.date.accessioned2021-07-15T12:17:35Z
dc.date.available2021-07-15T12:17:35Z
dc.date.issued2017
dc.description.abstractSince almost all datasets may be affected by the presence of anomalies which may skew the interpretation of data, outlier detection has become a crucial element of many datamining applications. Despite the fact that several methods of outlier detection have been proposed in the literature, there is still a need to look for new, more effective ones. This paper presents a new approach to outlier identification based on genetic algorithms. The study evaluates the performance and examines the features of several multiobjective genetic algorithms.en_EN
dc.identifier.citationDuraj, A., & Chomątek, Łukasz. (2017). Outlier Detection Using the Multiobjective Genetic Algorithm. Journal of Applied Computer Science, 25(2), 29-42. https://doi.org/10.34658/jacs.2017.2.29-42
dc.identifier.doihttps://doi.org/10.34658/jacs.2017.2.29-42
dc.identifier.doi10.34658/jacs.2017.2.29-42
dc.identifier.issn1507-0360
dc.identifier.urihttp://hdl.handle.net/11652/3877
dc.identifier.urihttps://doi.org/10.34658/jacs.2017.2.29-42
dc.language.isoenen_EN
dc.page.numbers. 29-42
dc.publisherWydawnictwo Politechniki Łódzkiejpl_PL
dc.publisherLodz University of Technology Pressen_EN
dc.relation.ispartofJournal of Applied Computer Science, Vol. 25, No. 2, Wydawnictwo Politechniki Łódzkiej, Łódź 2017, ISSN 1507-0360.
dc.rightsFair use conditionen_EN
dc.rightsDla wszystkich w zakresie dozwolonego użytkupl_PL
dc.rights.licenseLUT Licenseen_EN
dc.rights.licenseLicencja PŁpl_PL
dc.subjectoutliers detectionen_EN
dc.subjectgenetic algorithmen_EN
dc.subjectwykrywanie wartości odstającychpl_PL
dc.subjectalgorytm genetycznypl_PL
dc.titleOutlier Detection Using the Multiobjective Genetic Algorithmen_EN
dc.typeArtykułpl_PL
dc.typeArticleen_EN

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2017, Tom 25 Nr 2
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