Classifiers Fusion with Data Dependent Aggregation Schemes
Arūnas Lipnickas · 2002
In this paper we studied two different classifiers fusion algorithms exploiting the combination weights expressed over the entire data space and the combination with data dependent weights. The following aggregation schemes are employed in the study: the majority vote, the averaging, the combination via Choquet integral with the Lamda-fuzzy measure, the combination via space partitioning and classifier selection approach, and the combination via Choquet integral with the data dependent Lamda-fuzzy measure. 1.