A new artificial neural network ensemble based on feature selection and class recoding

M. P. Sesmero, J. M. Alonso-Weber, G. Gutiérrez, A. Ledezma, A. Sanchis
2010 Neural computing & applications (Print)  
Many of the studies related to supervised learning have focused on the resolution of multiclass problems. A standard technique used to resolve these problems is to decompose the original multiclass problem into multiple binary problems. In this paper, we propose a new learning model applicable to multi-class domains in which the examples are described by a large number of features. The proposed model is an Artificial Neural Network ensemble in which the base learners are composed by the union
more » ... a binary classifier and a multiclass classifier. To analyze the viability and quality of this system, it will be validated in two real domains: traffic sign recognition and hand-written digit recognition. Experimental results show that our model is at least as accurate as other methods reported in the bibliography but has a considerable advantage respecting size, computational complexity, and running time.
doi:10.1007/s00521-010-0458-5 fatcat:ifdwzzfocjdoxex4z6wivaap74