Outlier Mining Using the DBSCAN Algorithm
Data
2017
Tytuł czasopisma
ISSN czasopisma
Tytuł tomu
Wydawca
Wydawnictwo Politechniki Łódzkiej
Lodz University of Technology Press
Lodz University of Technology Press
Abstrakt
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.
Opis
Słowa kluczowe
outlier detection, similarity analysis, clustering, knowledge-based systems, wykrywanie wartości odstających, analiza podobieństwa, grupowanie, systemy oparte na wiedzy
Cytowanie
Nowak-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