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Different to other re-sampling ensemble learning, negative correlation learning trains all individual models in an ensemble simultaneously and cooperatively. In negative correlation learning, each individual could see all training data, and adapt its target function based on what the rest of individuals in the ensemble have learned. In this paper, two error bounds are introduced in negative correlation...
Ensemble learning system could lower down risk of overfitting that often appears in supervised learning for a single learning model. However, overfitting had still been observed in negative correlation learning that trains a set of neural networks simultaneously with correlation-based penalties. In negative correlation learning, each subsystem could see all training data, and focus on those data that...
Ensemble learning system could lessen the degree of overfitting that often appear in the supervised learning process for a single learning model. However, overfitting had still been observed in negative correlation learning that is an ensemble learning method with correlation-based penalty. Two constraints were introduced into negative correlation learning in order to conquer such overfitting. One...
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