Fundamentals of algorithmics
Fuzzy Sets and Systems - Special issue on fuzzy optimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ensembles of Learning Machines
WIRN VIETRI 2002 Proceedings of the 13th Italian Workshop on Neural Nets-Revised Papers
In Defense of One-Vs-All Classification
The Journal of Machine Learning Research
Engineering multiversion neural-net systems
Neural Computation
Generating an interpretable family of fuzzy partitions from data
IEEE Transactions on Fuzzy Systems
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We consider the problem of collective decision-making from an arbitrary set of classifiers under the Sugeno fuzzy integral (SFI). We assume that classifiers are given, i.e., they cannot be modified towards their effective combination. Under this baseline, we propose a selection-combination strategy, which separates the whole process into two stages: the classifiers selection, to discover a subset of cooperative classifiers under SFI, and the typical SFI combination of selected classifiers. The proposed selection is based on a greedy algorithm which through a heuristic allows an efficient search.