Analyzing Anti–correlation in Ensemble Learning
نویسندگان
چکیده
Anti–correlation has been used in training neural network ensembles. Negative correlation learning (NCL) is the state of the art anti–correlation measure. We propose an alternative anti–correlation measure, RTQRT–NCL, which shows signi£cant improvements on our test example, particularly with larger ensembles. We analyze the behavior of the negative correlation measure and derive a theoretical explanation of the improved performance of RTQRT–NCL in larger ensembles.
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تاریخ انتشار 2001