Outlier Mining Using the DBSCAN Algorithm

dc.contributor.authorNowak-Brzezińska, Agnieszka
dc.contributor.authorXięski, Tomasz
dc.date.accessioned2021-07-15T12:35:49Z
dc.date.available2021-07-15T12:35:49Z
dc.date.issued2017
dc.description.abstractThis paper introduces an approach to outlier mining in the context of a real-world dataset containing information about the mobile transceivers operation. The goal of the paper is to analyze the influence of using different similarity measures and multiple values of input parameters for the densitybased clustering algorithm on the number of outliers discovered during the mining process. The results of the experiments are presented in section 4 in order to discuss the significance of the analyzed parameters.en_EN
dc.identifier.citationNowak-Brzezińska, A., & Xięski, T. (2017). Outlier Mining Using the DBSCAN Algorithm. Journal of Applied Computer Science, 25(2), 53-68. https://doi.org/10.34658/jacs.2017.2.53-68
dc.identifier.doihttps://doi.org/10.34658/jacs.2017.2.53-68
dc.identifier.doi10.34658/jacs.2017.2.53-68
dc.identifier.issn1507-0360
dc.identifier.urihttp://hdl.handle.net/11652/3879
dc.identifier.urihttps://doi.org/10.34658/jacs.2017.2.53-68
dc.language.isoenen_EN
dc.page.numbers. 53-68
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.subjectoutlier detectionen_EN
dc.subjectsimilarity analysisen_EN
dc.subjectclusteringen_EN
dc.subjectknowledge-based systemsen_EN
dc.subjectwykrywanie wartości odstającychpl_PL
dc.subjectanaliza podobieństwapl_PL
dc.subjectgrupowaniepl_PL
dc.subjectsystemy oparte na wiedzypl_PL
dc.titleOutlier Mining Using the DBSCAN Algorithmen_EN
dc.typeArtykułpl_PL
dc.typeArticleen_EN

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