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    Feature Selection Based on Run Covering


    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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    Abstract

    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.

    Item Type: Book Section
    Additional Information: This paper was given at the 2006 IEEE Pacific-Rim Symposium on Image and Video Technology (PSIVT'06), November, 2006. This work is supported in part by Natural Science Foundation of China under grant 60305002, China/Ireland Science and Technology Research Collaboration Fund under grant CI-2004-09, and National Basic Research Program of China under grant 2006CB705700.
    Keywords: Feature Selection; Run Covering;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
    Item ID: 4914
    Identification Number: https://doi.org/10.1007/11949534_21
    Depositing User: Dr. Adam Winstanley
    Date Deposited: 25 Apr 2014 15:38
    Publisher: Springer Verlag
    Refereed: Yes
    URI:

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