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Published in:
2006 | OriginalPaper | Chapter
Pareto-Optimal Approaches to Neuro-Ensemble Learning
Author : Hussein Abbass
Published in: Multi-Objective Machine Learning
Publisher: Springer Berlin Heidelberg
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The whole is greater than the sum of the parts; this is the essence of using a mixture of classifiers instead of a single classifier. In particular, an ensemble of neural networks (we call neuro-ensemble) has attracted special attention in the machine learning literature. A set of trained neural networks are combined using a post-gate to form a single super-network. The three main challenges facing researchers in neuro-ensemble are:(1) which network to include in, or exclude from the ensemble; (2) how to define the size of the ensemble; (3) how to define diversity within the ensemble.