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ICMLA
2008
13 years 8 months ago
On the Use of Accuracy and Diversity Measures for Evaluating and Selecting Ensembles of Classifiers
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...
Tuve Löfström, Ulf Johansson, Henrik Bos...
ICASSP
2011
IEEE
12 years 11 months ago
Facial expression recognition using ensemble of classifiers
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...
FUZZIEEE
2007
IEEE
13 years 11 months ago
Ensembles of Fuzzy Classifiers
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...
ESANN
2004
13 years 8 months ago
Online policy adaptation for ensemble classifiers
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...
Christos Dimitrakakis, Samy Bengio
ICML
2002
IEEE
14 years 8 months ago
Is Combining Classifiers Better than Selecting the Best One
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...
Saso Dzeroski, Bernard Zenko