Discriminant Analysis Based on Nearest Feature Line

Lijun Yan, Cong Wang, Shu-Chuan Chu, Jeng-Shyang Pan

    Research output: Contribution to conferencePaperpeer-review

    9 Citations (Scopus)

    Abstract

    A novel feature extraction algorithm based on nearest feature line is proposed in this paper. The proposed algorithm can extract the local discriminant features of the samples. The performance of the proposed algorithm is directly associated with the parameter, so we use two discriminant power criterions to adaptively determine the parameter. Some experiments are implemented to evaluate the proposed algorithm and the experimental results demonstrate the efficiency of the proposed algorithm.

    Original languageEnglish
    Pages356-363
    Number of pages8
    DOIs
    Publication statusPublished - 1 Dec 2013
    EventThird Sino-foreign-interchange Workshop on Intelligence Science and Intelligent Data Engineering (IScIDE) -
    Duration: 15 Oct 2012 → …

    Conference

    ConferenceThird Sino-foreign-interchange Workshop on Intelligence Science and Intelligent Data Engineering (IScIDE)
    Period15/10/12 → …

    Keywords

    • Dimensionality reduction
    • Feature extraction
    • Nearest feature line

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