Multidimensional genetic programming for multiclass classification
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- @Article{LACAVA:2019:SEC,
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author = "William {La Cava} and Sara Silva and Kourosh Danai and
Lee Spector and Leonardo Vanneschi and Jason H. Moore",
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title = "Multidimensional genetic programming for multiclass
classification",
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journal = "Swarm and Evolutionary Computation",
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year = "2019",
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volume = "44",
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pages = "260--272",
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month = feb,
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keywords = "genetic algorithms, genetic programming, Multiclass
classification, Feature extraction, Feature selection,
Feature synthesis, Dimensionality reduction, M4GP",
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ISSN = "2210-6502",
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URL = "http://www.sciencedirect.com/science/article/pii/S2210650217309136",
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DOI = "doi:10.1016/j.swevo.2018.03.015",
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size = "20 pages",
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abstract = "We describe a new multiclass classification method
that learns multidimensional feature transformations
using genetic programming. This method optimizes models
by first performing a transformation of the feature
space into a new space of potentially different
dimensionality, and then performing classification
using a distance function in the transformed space. We
analyze a novel program representation for using
genetic programming to represent multidimensional
features and compare it to other approaches. Similarly,
we analyze the use of a distance metric for
classification in comparison to simpler techniques more
commonly used when applying genetic programming to
multiclass classification. Finally, we compare this
method to several state-of-the-art classification
techniques across a broad set of problems and show that
this technique achieves competitive test accuracies
while also producing concise models. We also quantify
the scalability of the method on problems of varying
dimensionality, sample size, and difficulty. The
results suggest the proposed method scales well to
large feature spaces",
- }
Genetic Programming entries for
William La Cava
Sara Silva
Kourosh Danai
Lee Spector
Leonardo Vanneschi
Jason H Moore
Citations