Metric-based methods, which use unlabeled data to detect gross differences in behavior away from the training points, have recently been introduced for model selection, often yielding very significant improvements over alternatives (including cross-validation). We introduce extensions that take...

This report presents and proposes several methods to improve the capacity of generalization of the learning algorithms in a context of financial decision-making. These methods, overall, aim at controlling the capacity of the learning algorithms in order to limit the problem of the over-training,...