This paper presents a cooperative coevolutive approach for designing neural network
ensembles. Cooperative coevolution is a recent paradigm in evolutionary computation that …

Abstract A Neural Network Ensemble (NNE) combines the outputs of several individually
trained neural networks in order to improve generalization performance. This article …

Current research is constantly producing an enormous amount of information, which
presents a challenge for data mining algorithms. Many of the problems in some of the most …

An enormous amount of information is continually being produced in current research, which
poses a challenge for data mining algorithms. Many of the problems in extremely active …

In this paper we present a cooperative coevolutive model for the evolution of neural network
topology and weights, called MOBNET. MOBNET evolves subcomponents that must be …

In this paper, we propose a new constructive method, based on cooperative coevolution, for
designing automatically the structure of a neural network for classification. Our approach is …

Instance selection is becoming increasingly relevant due to the huge amount of data that is
constantly produced in many fields of research. At the same time, most of the recent pattern …

Feature selection is one of the most important tasks in many machine learning and data
mining problems. Due to the increasing size of the problems, removing useless, erroneous …

In many real-world applications, pattern recognition systems are designed a priori using
limited and imbalanced data acquired from complex changing environments. Since new …

Learning and evolution are two fundamental forms of adaptation. There has been a great
interest in combining learning and evolution with neural networks in recent years. This paper …