The test set accuracy for ensembles of classifiers selected based on single measures of accuracy and diversity as well as combinations of such measures is investigated. It is foun...
This paper presents a novel method for facial expression classification that employs the combination of two different feature sets in an ensemble approach. A pool of base classi...
Thiago H. H. Zavaschi, Alessandro L. Koerich, Luiz...
The use of bagging is explored to create an ensemble of fuzzy classifiers. The learning algorithm used was ANFIS (Adaptive Neuro-Fuzzy Inference Systems). We compare results from b...
Juana Canul-Reich, Larry Shoemaker, Lawrence O. Ha...
Ensemble algorithms can improve the performance of a given learning algorithm through the combination of multiple base classifiers into an ensemble. In this paper, the idea of usin...
We empirically evaluate several state-of-theart methods for constructing ensembles of heterogeneous classifiers with stacking and show that they perform (at best) comparably to se...