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Negative correlation learning is an ensemble learning approach that is able to create negatively correlated learners simultaneously and cooperatively in a committee machine. One problem in negative correlation learning is that the learning error functions are defined in the same way for all individual learners. Learners have little choice in making their own decisions on how to learn a given data...
Self-awareness is a kind of ability of recognizing oneself as an individual being different from the environment and other individuals. This paper proposes negative correlation learning with self-awareness in order for each artificial neural network (ANN) in a committee machine to be self-aware in learning so that it could decide by itself to learn more or less. On one hand, when the learning would...
It has been shown that as the number of weak learners in a majority voting model is increased so does its generalization if those weak learners are uncorrelated or negatively correlated. Although some learning algorithms including bagging and boosting have been developed to create such weak learners, learners trained by these learning algorithms are actually not so weak in many applications. This...
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