Is combining classifiers with stacking better than selecting the best one?.

We empirically evaluate several state-of-the-art methods for constructing ensembles of heterogeneous classifiers with stacking and show that they perform (at best) comparably to selecting the best classifier from the ensemble by cross validation. Among state-of-the-art stacking methods, stacking wit...

Szczegółowa specyfikacja

Opis bibliograficzny

Wydane w:	Machine learning. 54, 3 (2004).
1. autor:	Dzeroski, Saso
Format:	Artykuł
Język:	English
Hasła przedmiotowe:	Multi-response model trees. Stacking. Combining classifiers. Ensembles of classifiers. Meta-learning.