Anti–correlation: A Diversity Promoting Mechanisms in Ensemble Learning
نویسندگان
چکیده
Abstract Anti–correlation has been used in training neural network ensembles. Negative correlation learning (NCL) is the state of the art anti–correlation measure. An alternative anti–correlation measure, RTQRT–NCL, which shows significant improvements on our test examples for both artificial neural networks (ANN) and genetic programming (GP) learning machines, is presented. We analyze the behavior of the negative correlation measure and derive a theoretical explanation of the improved performance of RTQRT– NCL in larger ensembles.
منابع مشابه
Anti–correlation: A Diversity Promoting Mechanism in Ensemble Learning
Anti–correlation has been used in training neural network ensembles. Negative correlation learning (NCL) is the state of the art anti–correlation measure. We present an alternative anti–correlation measure, RTQRT–NCL, which shows significant improvements on our test examples for both artificial neural networks (ANN) and genetic programming (GP) learning machines. We analyze the behavior of the ...
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تاریخ انتشار 2002