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Ensemble fuzzy classifiers design using weighted aggregation criteria

The rationale behind ensemble machine learning systems is the creation of many classifiers and the combination of their output such that the combination improves the performance of each single classifier. There are two key issues in the creation of ensemble classifiers: one is how two select and group the data samples to train the individual models and the other is how to select or combine the multiple outputs.