Grammar-Based Evolutionary Approach for Automatic Workflow Composition with Open Preprocessing Sequence
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{Barbudo:2021:SoCPaR,
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author = "Rafael Barbudo and Sebastian Ventura and
Jose Raul Romero",
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title = "Grammar-Based Evolutionary Approach for Automatic
Workflow Composition with Open Preprocessing Sequence",
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booktitle = "Proceedings of the 13th International Conference on
Soft Computing and Pattern Recognition (SoCPaR 2021)",
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year = "2021",
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editor = "Ajith Abraham and Andries Engelbrecht and
Fabio Scotti and Niketa Gandhi and Pooja Manghirmalani Mishra and
Giancarlo Fortino and Virgilijus Sakalauskas and
Sabri Pllana",
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volume = "417",
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series = "LNNS",
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pages = "647--656",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, Evolutionary
Algorithms, Grammar-Based Genetic Programming, TPOT",
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isbn13 = "978-3-030-96302-6",
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DOI = "doi:10.1007/978-3-030-96302-6_61",
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abstract = "Knowledge discovery is a complex process involving
several phases. Some of them are repetitive and
time-consuming, so they are susceptible of being
automated. As an example, the large number of machine
learning algorithms, together with their
hyper-parameters, constitutes a vast search space to
explore. In this vein, the term AutoML was coined to
encompass those approaches automating such phases. The
automatic workflow composition is an AutoML task that
involves both the selection and the hyper-parameter
optimisation of the algorithms addressing different
phases, thus giving a more comprehensive assistance
during the knowledge discovery process. Unlike other
proposals that predetermine the structure of the
preprocessing sequence, and in some cases the size of
the workflow, our proposal generates workflows made up
of an arbitrary number of preprocessing algorithms of
any type and a classifier. This allows returning more
accurate results since its avoids the
oversimplification of the solution space. The
optimisation is conducted by a grammar-guided genetic
programming algorithm. The proposal has been validated
and compared against TPOT and RECIPE generating
workflows with greater predictive performance.",
- }
Genetic Programming entries for
Rafael Barbudo Lunar
Sebastian Ventura
Jose Raul Romero Salguero
Citations