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Feature Selection Based on Run Covering |
Yang, Su; Liang, Jianning; Wang, Yuanyuan; Winstanley, Adam C.
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This paper proposes a new feature selection algorithm. First, the data
at every attribute are sorted. The continuously distributed data with the same
class labels are grouped into runs. The runs whose length is greater than a given
threshold are selected as “valid” runs, which enclose the instances separable
from the other classes. Second, we count how many runs cover every instance
and check how the covering number changes once eliminate a feature. Then, we
delete the feature that has the least impact on the covering cases for all
instances. We compare our method with ReliefF and a method based on mutual
information. Evaluation was performed on 3 image databases. Experimental
results show that the proposed method outperformed the other two.
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Keyword(s):
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Computer Science; National Center for Geocomputation, NCG; Feature Selection; Run Covering |
Publication Date:
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2006 |
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Type:
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Book chapter |
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Peer-Reviewed:
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Yes |
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Institution:
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Maynooth University |
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Citation(s):
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Yang, Su and Liang, Jianning and Wang, Yuanyuan and Winstanley, Adam C. (2006) Feature Selection Based on Run Covering. In: Lecture Notes in Computer Science. Lecture Notes in Computer Science, 4319 . Springer Verlag, Berlin, pp. 208-217. ISBN 978-3-540-68297-4 |
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Publisher(s):
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Springer Verlag |
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File Format(s):
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other |
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Related Link(s):
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http://mural.maynoothuniversity.ie/4914/1/AW_Feature_Selection.pdf |
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First Indexed:
2020-01-31 06:33:06 Last Updated:
2020-04-02 07:08:51 |
