Pruning GP-Based Classifier Ensembles by Bayesian Networks
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{conf/ppsn/StefanoFFF12,
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author = "Claudio {De Stefano} and Gianluigi Folino and
Francesco Fontanella and Alessandra {Scotto di Freca}",
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title = "Pruning {GP}-Based Classifier Ensembles by {Bayesian}
Networks",
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booktitle = "Parallel Problem Solving from Nature, PPSN XII (part
1)",
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year = "2012",
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editor = "Carlos A. {Coello Coello} and Vincenzo Cutello and
Kalyanmoy Deb and Stephanie Forrest and
Giuseppe Nicosia and Mario Pavone",
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volume = "7491",
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series = "Lecture Notes in Computer Science",
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pages = "236--245",
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address = "Taormina, Italy",
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month = sep # " 1-5",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-642-32936-4",
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DOI = "doi:10.1007/978-3-642-32937-1_24",
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size = "10 pages",
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abstract = "Classifier ensemble techniques are effectively used to
combine the responses provided by a set of classifiers.
Classifier ensembles improve the performance of single
classifier systems, even if a large number of
classifiers is often required. This implies large
memory requirements and slow speeds of classification,
making their use critical in some applications. This
problem can be reduced by selecting a fraction of the
classifiers from the original ensemble. In this work,
it is presented an ensemble-based framework that copes
with large datasets, however selecting a small number
of classifiers composing the ensemble. The framework is
based on two modules: an ensemble-based Genetic
Programming (GP) system, which produces a high
performing ensemble of decision tree classifiers, and a
Bayesian Network (BN) approach to perform classifier
selection. The proposed system exploits the advantages
provided by both techniques and allows to strongly
reduce the number of classifiers in the ensemble.
Experimental results compare the system with well-known
techniques both in the field of GP and BN and show the
effectiveness of the devised approach. In addition, a
comparison with a pareto optimal strategy of pruning
has been performed.",
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bibsource = "DBLP, http://dblp.uni-trier.de",
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affiliation = "Universita di Cassino e del Lazio Meridionale, Italy",
- }
Genetic Programming entries for
Claudio De Stefano
Gianluigi Folino
Francesco R Fontanella
Alessandra Scotto di Freca
Citations