Szczegóły publikacji
Opis bibliograficzny
Radial-based approach to imbalanced data oversampling / Michał Koziarski, Bartosz Krawczyk, Michał Woźniak // W: HAIS 2017 : Hybrid Artificial Intelligent Systems : 12th international conference : La Rioja, Spain, June 21-23, 2017 : proceedings / eds. Francisco Javier Martínez de Pisón, [et al.]. — Cham : Springer International Publishing AG, cop. 2017. — (Lecture Notes in Computer Science ; ISSN 0302-9743. Lecture Notes in Artificial Intelligence ; LNAI 10334). — ISBN: 978-3-319-59649-5; e-ISBN: 978-3-319-59650-1. — S. 318–327. — Bibliogr. s. 326–327, Abstr. — Publikacja dostępna online od: 2017-06-02. — M. Koziarski - afiliacja: Wrocław University of Science and Technology
Autorzy (3)
- Koziarski Michał
- Krawczyk Bartosz
- Woźniak Michał
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 115438 |
|---|---|
| Data dodania do BaDAP | 2018-07-30 |
| Tekst źródłowy | URL |
| DOI | 10.1007/978-3-319-59650-1_27 |
| Rok publikacji | 2017 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | International Conference on Hybrid Artificial Intelligence Systems 2017 |
| Czasopismo/seria | Lecture Notes in Computer Science |
Abstract
The difficulty of the many practical decision problem lies in the nature of analyzed data. One of the most important real data characteristic is imbalance among examples from different classes. Despite more than two decades of research, imbalanced data classification is still one of the vital challenges to be addressed. The traditional classification algorithms display strongly biased performance on imbalanced datasets. One of the most popular way to deal with such a problem is to modify the learning set to decrease disproportion between objects from different classes using over- or undersampling approaches. In this work a novel preprocessing technique for imbalanced datasets is presented, which takes into consideration the mutual density class distribution. The proposed approach has been evaluated on the basis of the computer experiments carried out on the benchmark datasets. Their results seem to confirm the usefulness of the proposed concept in comparison to the state-of-art methods.
