Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Vladislavleva:2010:EuroGP,
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author = "Katya Vladislavleva and Kalyan Veeramachaneni and
Una-May O'Reilly",
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title = "Learning a Lot from Only a Little: Genetic Programming
for Panel Segmentation on Sparse Sensory Evaluation
Data",
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booktitle = "Proceedings of the 13th European Conference on Genetic
Programming, EuroGP 2010",
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year = "2010",
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editor = "Anna Isabel Esparcia-Alcazar and Aniko Ekart and
Sara Silva and Stephen Dignum and A. Sima Uyar",
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volume = "6021",
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series = "LNCS",
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pages = "244--255",
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address = "Istanbul",
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month = "7-9 " # apr,
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organisation = "EvoStar",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, Symbolic
regression, Pareto GP, panel segmentation, survey
modeling, hedonic, sensory evaluation, GP, ensembles",
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isbn13 = "978-3-642-12147-0",
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DOI = "doi:10.1007/978-3-642-12148-7_21",
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abstract = "We describe a data mining framework that derives
panelist information from sparse flavour survey data.
One component of the framework executes genetic
programming ensemble based symbolic regression. Its
evolved models for each panelist provide a second
component with all plausible and uncorrelated
explanations of how a panelist rates flavours. The
second component bootstraps the data using an ensemble
selected from the evolved models, forms a probability
density function for each panelist and clusters the
panelists into segments that are easy to please,
neutral, and hard to please.",
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notes = "Part of \cite{Esparcia-Alcazar:2010:GP} EuroGP'2010
held in conjunction with EvoCOP2010 EvoBIO2010 and
EvoApplications2010",
- }
Genetic Programming entries for
Ekaterina (Katya) Vladislavleva
Kalyan Veeramachaneni
Una-May O'Reilly
Citations