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[ 1 ] - استفاده از یادگیری همبستگی منفی در بهبود کارایی ترکیب شبکه های عصبی

This paper investigates the effect of diversity caused by Negative Correlation Learning(NCL) in the combination of neural classifiers and presents an efficient way to improve combining performance. Decision Templates and Averaging, as two non-trainable combining methods and Stacked Generalization as a trainable combiner are investigated in our experiments . Utilizing NCL for diversifying the ba...