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Abstract: Recent research has proved the benefits of the use of ensembles of classifiers for classification problems. Ensembles of classifiers can be constructed by a number of methods manipulating the training set with the purpose of creating a set of diverse and accurate base classifiers. One way to manipulate the training set for construction of the base classifiers is to apply feature selection. In this paper we evaluate the contextual merit measure as a feature selection heuristic for ensemble... (Update)
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Diversity in Ensemble Feature Selection - Tsymbal, Pechenizkiy, Cunningham (2003) (Correct)
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2: Integrating multiple classifiers by finding their areas of expertise - Koppel, Engelson - 1996
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BibTeX entry: (Update)
Tsymbal, A., Puuronen, S., Skrypnyk, I.: Ensemble feature selection with dynamic integration of classifiers, In: Proc. Int. ICSC Congress on Computational Intelligence Methods and Applications CIMA'2001, Bangor, Wales, U.K. (2001). http://citeseer.ist.psu.edu/tsymbal01ensemble.html More
@misc{ tsymbal01ensemble,
author = "A. Tsymbal and S. Puuronen and I. Skrypnyk",
title = "Ensemble feature selection with dynamic integration of classifiers",
text = "Tsymbal, A., Puuronen, S., Skrypnyk, I.: Ensemble feature selection with
dynamic integration of classifiers, In: Proc. Int. ICSC Congress on Computational
Intelligence Methods and Applications CIMA'2001, Bangor, Wales, U.K. (2001).",
year = "2001",
url = "citeseer.ist.psu.edu/tsymbal01ensemble.html" }
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