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    Kernel-based distance metric learning for microarray data classification

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    1471-2105-7-299.pdf (345.8Kb)
    Issue Date
    2006-06
    Author
    Xiong, Huilin
    Chen, Xue-wen
    Publisher
    BIOMED CENTRAL LTD
    Type
    Article
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    Abstract
    Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with traditional pattern classifications, gene expression-based data classification is typically characterized by high dimensionality and small sample size, which make the task quite challenging. Results: In this paper, we present a modified K-nearest-neighbor (KNN) scheme, which is based on learning an adaptive distance metric in the data space, for cancer classification using microarray data. The distance metric, derived from the procedure of a data-dependent kernel optimization, can substantially increase the class separability of the data and, consequently, lead to a significant improvement in the performance of the KNN classifier. Intensive experiments show that the performance of the proposed kernel-based KNN scheme is competitive to those of some sophisticated classifiers such as support vector machines (SVMs) and the uncorrelated linear discriminant analysis (ULDA) in classifying the gene expression data. Conclusion: A novel distance metric is developed and incorporated into the KNN scheme for cancer classification. This metric can substantially increase the class separability of the data in the feature space and, hence, lead to a significant improvement in the performance of the KNN classifier.
    URI
    http://hdl.handle.net/1808/1514
    DOI
    https://doi.org/10.1186/1471-2105-7-299
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    • Electrical Engineering and Computer Science Scholarly Works [302]
    Citation
    Xiong, Huilin, and Xue-wen Chen. 2006. “Kernel-Based Distance Metric Learning for Microarray Data Classification.” BMC Bioinformatics 7:299. http://dx.doi.org/10.1186/1471-2105-7-299.

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    Lawrence, KS 66045
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    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

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