The Role of Diversity in Ensemble Learning

Modified: 2016/02/16 17:09 by admin - Uncategorized
Ensemble learning is a machine learning paradigm that achieves the state-of-the-art performance. Diversity was believed to be a key to a good performance of an ensemble approach, which, however, previously served only as a heuristic idea. We show that diversity can play the role of regularization.


  • Diversity regularized machine: In the IJCAI'11 (PDF) paper, we showed that diversity plays a role of regularization as in popular statistical learning approaches.

  • Diversity regularized ensemble pruning: In the ECML'12 (PDF) paper, we proved that diversity defined on hypothesis output space plays a role of regularization, and use this principle to prune Bagging classifiers.


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