Interactive Exploratory Data Analysis
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{malinchik:2004:ieda,
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title = "Interactive Exploratory Data Analysis",
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author = "Sergey Malinchik and Belinda Orme and
Joseph Rothermich and Eric Bonabeau",
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pages = "1098--1104",
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booktitle = "Proceedings of the 2004 IEEE Congress on Evolutionary
Computation",
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year = "2004",
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publisher = "IEEE Press",
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month = "20-23 " # jun,
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address = "Portland, Oregon",
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ISBN = "0-7803-8515-2",
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keywords = "genetic algorithms, genetic programming, Real-world
applications",
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DOI = "doi:10.1109/CEC.2004.1330984",
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abstract = "We illustrate with two simple examples how Interactive
Evolutionary Computation (IEC) can be applied to
Exploratory Data Analysis (EDA). IEC is valuable in an
EDA context because the objective function is by
definition either unknown a priori or difficult to
formalize. In the first example IEC is used to evolve
the {"}true{"} metric of attribute space. The goal here
is to evolve the attribute space distance function
until {"}interesting{"} features of the data are
revealed when a clustering algorithm is applied. In a
second example, we show how a user can interactively
evolve an auditory display of cluster data. In this
example, we use IEC with Genetic Programming to evolve
a mapping of data to sound for sonifying qualities of
data clusters.",
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notes = "CEC 2004 - A joint meeting of the IEEE, the EPS, and
the IEE.",
- }
Genetic Programming entries for
Sergey Malinchik
Belinda Orme
Joseph A Rothermich
Eric Bonabeau
Citations