Baza Publikacji Pracowników Politechniki Lubelskiej

Status:
Autorzy:	Rachwał Alicja, Karczmarek Paweł, Rachwał Albert
Dyscypliny:
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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.

Smooth Ordered Weighted Averaging operators