- An ideal ensemble is composed of base classifiers that perform well and that have minimal overlap in their errors. Eliminating classifiers from an ensemble based on a criterion t...
In this paper we propose a meta-evolutionary approach to improve on the performance of individual classifiers. In the proposed system, individual classifiers evolve, competing to ...
Cluster ensembles are collections of individual solutions to a given clustering problem which are useful or necessary to consider in a wide range of applications. The R package˜c...
The results of knowledge discovery in databases could vary depending on the data mining method. There are several ways to select the most appropriate data mining method dynamicall...
Seppo Puuronen, Vagan Y. Terziyan, Alexander Logvi...
Abstract. Ensemble methods can achieve excellent performance relying on member classifiers’ accuracy and diversity. We conduct an empirical study of the relationship of ensemble...