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Title:
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FEATURE RANKING BASED ON WEIGHTS ESTIMATED BY MULTIOBJECTIVE OPTIMIZATION |
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Author(s):
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Daniela Zaharie , Diana Lungeanu , Stefan Holban |
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ISBN:
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978-972-8924-40-9 |
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Editors:
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Jörg Roth, Jairo Gutiérrez and Ajith P. Abraham (series editors: Piet Kommers, Pedro Isaías and Nian-Shing Chen) |
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Year:
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2007 |
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Edition:
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Single |
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Keywords:
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Feature selection, feature ranking, ranking aggregation, multi-objective optimization, evolutionary algorithms, distributed
data mining. |
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Type:
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Short Paper |
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First Page:
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124 |
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Last Page:
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128 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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The aim of this paper is twofold. On the one hand, we analyze a feature ranking technique based on the weights estimated
by an evolutionary algorithm for multiobjective optimization. On the other hand, we address the problem of comparing
and aggregating different rankings obtained either by applying different methods to the same dataset, or by applying, in
the context of distributed data mining tasks, the same method to different datasets. |
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