This paper studies the ensemble selection problem for unsupervised learning. Given a large library of different clustering solutions, our goal is to select a subset of solutions t...
Abstract. Ensemble selection deals with the reduction of an ensemble of predictive models in order to improve its efficiency and predictive performance. A number of ensemble select...
Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. ...
Various methods for ensemble selection and classifier combination have been designed to optimize the results of ensembles of classifiers. Genetic algorithm (GA) which uses the div...
Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souz...
We investigate four previously unexplored aspects of ensemble selection, a procedure for building ensembles of classifiers. First we test whether adjusting model predictions to p...
Rich Caruana, Art Munson, Alexandru Niculescu-Mizi...
We present a method for constructing ensembles from libraries of thousands of models. Model libraries are generated using different learning algorithms and parameter settings. For...
Rich Caruana, Alexandru Niculescu-Mizil, Geoff Cre...