Interactive Exploratory Data Analysis

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{malinchik:2004:ieda,
  title =        "Interactive Exploratory Data Analysis",
  author =       "Sergey Malinchik and Belinda Orme and 
                 Joseph Rothermich and Eric Bonabeau",
  pages =        "1098--1104",
  booktitle =    "Proceedings of the 2004 IEEE Congress on Evolutionary
                 Computation",
  year =         "2004",
  publisher =    "IEEE Press",
  month =        "20-23 " # jun,
  address =      "Portland, Oregon",
  ISBN =         "0-7803-8515-2",
  keywords =     "genetic algorithms, genetic programming, Real-world
                 applications",
  DOI =          "doi:10.1109/CEC.2004.1330984",
  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.",
  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