M3GP: Multiclass Classification with GP
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gp-bibliography.bib Revision:1.5787
- @InProceedings{Munoz:2015:EuroGP,
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author = "Luis Munoz and Sara Silva and Leonardo Trujillo",
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title = "{M3GP:} Multiclass Classification with {GP}",
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booktitle = "18th European Conference on Genetic Programming",
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year = "2015",
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editor = "Penousal Machado and Malcolm I. Heywood and
James McDermott and Mauro Castelli and
Pablo Garcia-Sanchez and Paolo Burelli and Sebastian Risi and Kevin Sim",
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series = "LNCS",
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volume = "9025",
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publisher = "Springer",
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pages = "78--91",
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address = "Copenhagen",
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month = "8-10 " # apr,
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organisation = "EvoStar",
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keywords = "genetic algorithms, genetic programming,
Classification, Multiple classes, Multidimensional
clustering",
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isbn13 = "978-3-319-16500-4",
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DOI = "
doi:10.1007/978-3-319-16501-1_7",
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abstract = "Data classification is one of the most ubiquitous
machine learning tasks in science and engineering.
However, Genetic Programming is still not a popular
classification methodology, partially due to its poor
performance in multiclass problems. The recently
proposed Multidimensional Multiclass Genetic
Programming algorithm achieved promising results in
this area, by evolving mappings of the p-dimensional
data into a d-dimensional space, and applying a minimum
Mahalanobis distance classifier. Despite good
performance, M2GP employs a greedy strategy to set the
number of dimensions d for the transformed data, and
fixes it at the start of the search, an approach that
is prone to locally optimal solutions. This work
presents the M3GP algorithm, that stands for M2GP with
multidimensional populations. M3GP extends M2GP by
allowing the search process to progressively search for
the optimal number of new dimensions d that maximise
the classification accuracy. Experimental results show
that M3GP can automatically determine a good value for
d depending on the problem, and achieves excellent
performance when compared to state-of-the-art-methods
like Random Forests, Random Subspaces and Multilayer
Perceptron on several benchmark and real-world
problems.",
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notes = "Part of \cite{Machado:2015:GP} EuroGP'2015 held in
conjunction with EvoCOP2015, EvoMusArt2015 and
EvoApplications2015",
- }
Genetic Programming entries for
Luis Munoz Delgado
Sara Silva
Leonardo Trujillo
Citations