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  • Improved direct LDA and its application to DNA microarray gene expression data

    Author(s)
    Paliwal, Kuldip K
    Sharma, Alok
    Griffith University Author(s)
    Paliwal, Kuldip K.
    Year published
    2010
    Metadata
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    Abstract
    The direct linear discriminant analysis (DLDA) technique is a well known technique for dimensionality reduction. It can overcome the small sample size problem. However, its performance is limited. In this paper we address its drawbacks and propose an improvement of the DLDA technique. The experiment is conducted on several DNA microarray gene expression datasets and the performance (in terms of classification accuracy) of the proposed improvement of the technique is reported at 91.1% which is very promising.The direct linear discriminant analysis (DLDA) technique is a well known technique for dimensionality reduction. It can overcome the small sample size problem. However, its performance is limited. In this paper we address its drawbacks and propose an improvement of the DLDA technique. The experiment is conducted on several DNA microarray gene expression datasets and the performance (in terms of classification accuracy) of the proposed improvement of the technique is reported at 91.1% which is very promising.
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    Journal Title
    Pattern Recognition Letters
    Volume
    31
    Issue
    16
    DOI
    https://doi.org/10.1016/j.patrec.2010.08.003
    Subject
    Artificial intelligence not elsewhere classified
    Cognitive and computational psychology
    Publication URI
    http://hdl.handle.net/10072/37823
    Collection
    • Journal articles

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