2017, Tom 25 Nr 2

Stały URI dla kolekcjihttp://hdl.handle.net/11652/3827

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20171

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Autorsearch.filters.applied.operator.equals: search.filters.author.Xięski, TomaszTematsearch.filters.applied.operator.equals: search.filters.subject.knowledge-based systems

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  • Pozycja
    Outlier Mining Using the DBSCAN Algorithm
    (Wydawnictwo Politechniki Łódzkiej, 2017) Nowak-Brzezińska, Agnieszka; Xięski, Tomasz
    This 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.