Fuzzy integral based data fusion for protein function prediction

Abstract

Data fusion using diverse biological data has been applied to predict the protein function in recent years. In this paper, fuzzy integral fusion based on fuzzy measure is used to integrate the probabilistic outputs of different classifiers. Support vector machines as base learners are applied to predict the functions of examples from each data source. Fuzzy density values are determined by Particle Swarm Algorithm and an improved λ-measure is used. We compare our improved fuzzy measure to typical one. The experimental results show that our method has the better results. © 2011 Springer-Verlag.