Outlier Detection Using the Multiobjective Genetic Algorithm
Data
2017
Autorzy
Tytuł czasopisma
ISSN czasopisma
Tytuł tomu
Wydawca
Wydawnictwo Politechniki Łódzkiej
Lodz University of Technology Press
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