We analyze the formal grounding behind Negative Correlation (NC) Learning, an ensemble learning technique developed in the evolutionary computation literature. We show that by rem...
Abstract. The concept of Ensemble Learning has been shown to increase predictive power over single base learners. Given the bias-variancecovariance decomposition, diversity is char...
Abstract. In Machine Learning, ensembles are combination of classifiers. Their objective is to improve the accuracy. In previous works, we have presented a method for the generati...
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...