TUNING DIVERSITY IN BAGGED ENSEMBLES
John G. Carney, Pádraig Cunningham · International Journal of Neural Systems · 2000
In this paper, we investigate how the level of diversity amongst individual neural networks in a bagged ensemble can significantly influence overall ensemble generalization performance. We propose a new technique that tunes this diversity so that ensemble generalization performance is optimized and evaluate its performance on benchmark regression data-sets.