Article,

Anti-correlation: A Diversity Promoting Mechanisms in Ensemble Learning

, and .
The Australian Journal of Intelligent Information Processing Systems, 7 (3/4): 139--149 (2001)

Abstract

Anticorrelation has been used in training neural network ensembles. Negative correlation learning (NCL) is the state of the art anticorrelation measure. We present an alternative anticorrelation measure, RTQRTNCL, which shows significant improvements on our test examples for both artificial neural networks (ANN) and genetic programming (GP) learning machines. We analyse the behaviour of the negative correlation measure and derive a theoretical explanation of the improved performance of RTQRTNCL in larger ensembles.

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