A Novel Approach on Behavior of Sleepy Lizards Based on K-Nearest Neighbor Algorithm

Lin-Lin Tang, Jeng-Shyang Pan, XiaoLv Guo, Shu-Chuan Chu, John Roddick

    Research output: Chapter in Book/Report/Conference proceedingChapter

    2 Citations (Scopus)

    Abstract

    The K-Nearest Neighbor algorithm is one of the commonly used methods for classification in machine learning and computational intelligence. A new research method and its improvement for the sleepy lizards based on the K-Nearest Neighbor algorithm and the traditional social network algorithms are proposed in this chapter. The famous paired living habit of sleepy lizards is verified based on our proposed algorithm. In addition, some common population characteristics of the lizards are also introduced by using the traditional social net work algorithms. Good performance of the experimental results shows efficiency of the new research method.

    Original languageEnglish
    Title of host publicationSocial Networks: A Framework of Computational Intelligence
    Subtitle of host publicationA Framework of Computational Intelligence
    PublisherSpringer
    Pages287-311
    Number of pages25
    Volume526
    ISBN (Print)9783319029924
    DOIs
    Publication statusPublished - 2014

    Publication series

    NameStudies in Computational Intelligence
    Volume526
    ISSN (Print)1860-949X

    Keywords

    • Computational intelligence
    • K-Nearest neighbor (KNN) algorithm
    • Sleep lizard
    • Social network analysis (SNA)

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  • Cite this

    Tang, L-L., Pan, J-S., Guo, X., Chu, S-C., & Roddick, J. (2014). A Novel Approach on Behavior of Sleepy Lizards Based on K-Nearest Neighbor Algorithm. In Social Networks: A Framework of Computational Intelligence: A Framework of Computational Intelligence (Vol. 526, pp. 287-311). (Studies in Computational Intelligence; Vol. 526). Springer. https://doi.org/10.1007/978-3-319-02993-1_13