Wpływ metody łączenia modeli na wielkość błędu klasyfikacji w podejściu wielomodelowym - Gatnar, Eugeniusz (The Impact of Combination Function on the Classification Error in Classifier Fusion, 2008)
Classifier combining is an important method in a nonparametric discriminant analysis. In this approach M base (local) models are combined into the aggregated (global) model with the use of the combination function Ψ: D*(xi.) = Ψ (D1(xi), ..., DM (xi)), where Dm(x) is the prediction of the m-th base model. Several different types of the function Ψ can be found in the literature. The most commonly used are: majority vote, average, maximum and product. Moreover, some more sophisticated combination functions have been proposed, such as fuzzy integrals or decision templates. In this paper ten combination functions Ψ have been compared and their impact on the classification error of the model D* has been investigated.
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu = Research Papers of Wrocław University of Economics; 2008; Nr 7, s. 89-98