Outlier Detection Using the Multiobjective Genetic Algorithm

Miniatura

Pliki

2_Outlier_detection_Duraj_2017.pdf (156.63 KB)

Data

2017

Autorzy

Tytuł czasopisma

ISSN czasopisma

Tytuł tomu

Wydawca

Wydawnictwo Politechniki Łódzkiej
Lodz University of Technology Press

Abstrakt

Since 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.

Opis

Słowa kluczowe

outliers detection, genetic algorithm, wykrywanie wartości odstających, algorytm genetyczny

Cytowanie

Duraj, 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

URI

http://hdl.handle.net/11652/3877
 https://doi.org/10.34658/jacs.2017.2.29-42

Kolekcje

2017, Tom 25 Nr 2
Artykuły (WFTIiMS)