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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Classification Ensemble by Genetic Algorithms
verfasst von : Hamid Parvin, Behrouz Minaei, Akram Beigi, Hoda Helmi
Erschienen in: Adaptive and Natural Computing Algorithms
Verlag: Springer Berlin Heidelberg
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Different classifiers with different characteristics and methodologies can complement each other and cover their internal weaknesses; Thus Classifier ensemble is an important approach to handle the drawback. If an automatic and fast method is obtained to approximate the accuracies of different classifiers on a typical dataset, the learning can be converted to an optimization problem and genetic algorithm is an important approach in this way. We proposed a selection method for classification ensemble by applying GA for improving performance of classification. CEGA is examined on some datasets and it considerably shows improvements.