Training Distributed GP Ensemble With a Selective Algorithm Based on Clustering and Pruning for Pattern Classification
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- @Article{Folino:2008:TEC,
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author = "Gianluigi Folino and Clara Pizzuti and
Giandomenico Spezzano",
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title = "Training Distributed GP Ensemble With a Selective
Algorithm Based on Clustering and Pruning for Pattern
Classification",
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journal = "IEEE Transactions on Evolutionary Computation",
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year = "2008",
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month = aug,
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volume = "12",
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number = "4",
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pages = "458--468",
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keywords = "genetic algorithms, genetic programming, boosting
algorithm, cellular genetic programming, decision
trees, distributed hybrid environment, fittest trees,
pattern classification, pruning strategies, training
distributed GP ensemble, decision trees, pattern
classification",
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DOI = "doi:10.1109/TEVC.2007.906658",
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ISSN = "1089-778X",
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abstract = "A boosting algorithm based on cellular genetic
programming (GP) to build an ensemble of predictors is
proposed. The method evolves a population of trees for
a fixed number of rounds and, after each round, it
chooses the predictors to include in the ensemble by
applying a clustering algorithm to the population of
classifiers. Clustering the population allows the
selection of the most diverse and fittest trees that
best contribute to improve classification accuracy. The
method proposed runs on a distributed hybrid
environment that combines the island and cellular
models of parallel GP. The combination of the two
models provides an efficient implementation of
distributed GP, and, at the same time, the generation
of low sized and accurate decision trees. The large
amount of memory required to store the ensemble affects
the performance of the method. This paper shows that,
by applying suitable pruning strategies, it is possible
to select a subset of the classifiers without
increasing misclassification errors; indeed for some
data sets, for up to 30percent of pruning, ensemble
accuracy increases. Experimental results show that the
combination of clustering and pruning enhances
classification accuracy of the ensemble approach.",
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notes = "Also known as \cite{4439200}",
- }
Genetic Programming entries for
Gianluigi Folino
Clara Pizzuti
Giandomenico Spezzano
Citations