Application of Choquet Integral to Efficient Aggregation of Neural Networks

Abstract

This paper presents a novel application of fuzzy integral to combine multiple neural networks subjectively. The concept of combining multiple neural networks or classifiers has been largely exploited in the fields of artificial neural networks and pattern recognition. The proposed method based on Choquet integral nonlinearly combines the outputs of the networks with subjective evaluation of the reliability of the individual neural networks. Experimental results with the recognition problem of totally unconstrained handwritten numerals show that the performance of the proposed method outperforms that of the conventional methods.