Smooth Ordered Weighted Averaging operators
Artykuł w czasopiśmie
MNiSW
5
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| Status: | |
| Autorzy: | Rachwał Alicja, Karczmarek Paweł, Rachwał Albert |
| Dyscypliny: | |
| Aby zobaczyć szczegóły należy się zalogować. | |
| Rok wydania: | 2025 |
| Wersja dokumentu: | Elektroniczna |
| Język: | angielski |
| Wolumen/Tom: | 686 |
| Numer artykułu: | 121343 |
| Strony: | 1 - 16 |
| Web of Science® Times Cited: | 0 |
| Scopus® Cytowania: | 0 |
| Bazy: | Web of Science | Scopus |
| Efekt badań statutowych | NIE |
| Finansowanie: | The research was financed from the internal Fund of the Scientific Discipline (Grants no. FD-20/IT-3/004 and FD-20/IT-3/055) |
| Materiał konferencyjny: | NIE |
| Publikacja OA: | NIE |
| Abstrakty: | angielski |
| The study demonstrates the application of OWA operators to binary and multiclass classification problems and seeks a way to improve classification accuracy using smoothing methods. OWA operators are used to aggregate class membership probabilities obtained from individual classifiers. Smoothing methods inspired by Newton-Cotes quadratures are applied before the aggregation step to improve the quality of the final results. Moreover, several sets of weights are used for OWA operators, including sets of weights based on the accuracy of individual classifiers. The experiments are conducted on 20 datasets, from which 7 are designed for binary classification and the rest are for multiclass classification. A comparison of the average accuracy for different sets of weights is shown. On the basis of experimental results, smoothing methods that significantly improve classification accuracy are identified. |
