Using Shadowed Clustering and Breeder GA in the Imbalanced Data Classification Problems (CROSBI ID 628160)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Panjkota, Ante ; Stančić, Ivo ; Musić, Josip ; Drole, Miha ; Vračar, Petar ; Kononenko, Igor ; Kukar, Matjaž
engleski
Using Shadowed Clustering and Breeder GA in the Imbalanced Data Classification Problems
We discuss possibilities and advantages of using a novel oversampling approach based on the synthetic minority instances generation by using shadowed clustering and Breeder genetic algorithm for dealing with imbalanced classification problems. Viability of the proposed oversampling method is confirmed through comparison with state-of-the-algorithms in experiments on four imbalanced datasets obtained from a Blender-based simulator. In all conducted experiments the proposed oversampling approach performs at least as well as state-of the-art algorithms. Our results indicate a great potential for future ensemble algorithm formed from orthogonal projections and oversampled as proposed in this.
Cluster Analysis; Feature selection; Imbalanced data classification; minority class oversampling; ensembles for classification
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Podaci o prilogu
88-91.
2015.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 18th International Multiconference INFORMATION SOCIETY – IS 2015 Volume A (Intelligent Systems)
Piltaver, Rok ; Gams, Matjaž
Ljubljana: Institut Jožef Stefan
Podaci o skupu
INFORMATION SOCIETY – IS 2015 (Intelligent Systems)
predavanje
07.10.2015-07.10.2015
Ljubljana, Slovenija