This paper discusses the issues that arise in the design and implementation of an industrialstrength evolutionary-based system for the optimization of the monthly work schedules f...
Neural network ensemble is a learning paradigm where several neural networks are jointly used to solve a problem. In this paper, the relationship between the generalization abilit...
Background: Recently several statistical methods have been proposed to identify genes with differential expression between two conditions. However, very few studies consider the p...
— Both theory and a wealth of empirical studies have established that ensembles are more accurate than single predictive models. Unfortunately, the problem of how to maximize ens...
This paper studies the ensemble selection problem for unsupervised learning. Given a large library of different clustering solutions, our goal is to select a subset of solutions t...