Outlier Mining Using the DBSCAN Algorithm

Miniatura

Pliki

4_Outlier_mining_Xięski_2017.pdf (172.88 KB)

Data

2017

Autorzy

Tytuł czasopisma

ISSN czasopisma

Tytuł tomu

Wydawca

Wydawnictwo Politechniki Łódzkiej
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

URI

http://hdl.handle.net/11652/3879
 https://doi.org/10.34658/jacs.2017.2.53-68

Kolekcje

2017, Tom 25 Nr 2