The Landscape Contest at ICPR 2010

The landscape contest provides a new and configurable framework to evaluate the robustness of supervised classification techniques and detect their limitations. By means of an evolutionary multiobjective optimization approach, artificial data sets are generated to cover reachable regions in differen...

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Bibliographic Details
Published inRecognizing Patterns in Signals, Speech, Images and Videos pp. 29 - 45
Main Authors Macià, Núria, Ho, Tin Kam, Orriols-Puig, Albert, Bernadó-Mansilla, Ester
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2010
SeriesLecture Notes in Computer Science
Online AccessGet full text
ISBN9783642177101
3642177107
ISSN0302-9743
1611-3349
DOI10.1007/978-3-642-17711-8_4

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Summary:The landscape contest provides a new and configurable framework to evaluate the robustness of supervised classification techniques and detect their limitations. By means of an evolutionary multiobjective optimization approach, artificial data sets are generated to cover reachable regions in different dimensions of data complexity space. Systematic comparison of a diverse set of classifiers highlights their merits as a function of data complexity. Detailed analysis of their comparative behavior in different regions of the space gives guidance to potential improvements of their performance. In this paper we describe the process of data generation and discuss performances of several well-known classifiers as well as the contestants’ classifiers over the obtained data sets.
ISBN:9783642177101
3642177107
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-17711-8_4