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Erschienen in:
2011 | OriginalPaper | Buchkapitel
The Committee of Experts Approach: Ensemble Learning
verfasst von : Bruno Baruque, Emilio Corchado
Erschienen in: Fusion Methods for Unsupervised Learning Ensembles
Verlag: Springer Berlin Heidelberg
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The main concept behind ensemble learning model is the simple intuitive idea of a committee of experts working together to solve a problem.
In all likelihood, when dealing with a complicated problem, a group of experts with varied experience in the same area will have a higher probability of reaching a satisfactory solution than a single expert. All members contribute their own experience and initiatives and the group as a whole can choose to uphold or to reject a new idea on its own merits.
In the field of AI, ensemble learning is the process by which multiple models, such as classifiers or experts, are strategically generated and combined to solve a particular computational intelligence problem. Ensemble learning is primarily used to improve the performance -classification, prediction, function approximation, etc.- of a model, or reduce the likelihood of an unfortunate selection of a poor one.