Interactive Exploratory Data Analysis

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@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