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.
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Acknowledgments
The authors would like to thank the reviewers for providing very helpful comments and suggestions. The authors would also like to thank for the support from the project named Research on Multiple Description Coding Frames with Watermarking Techniques in Wavelet Domain which belongs to the NSFC (National Natural Science Foundation of China) with the Grant number 61202456.
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Tang, LL., Pan, JS., Guo, X., Chu, SC., Roddick, J.F. (2014). A Novel Approach on Behavior of Sleepy Lizards Based on K-Nearest Neighbor Algorithm. In: Pedrycz, W., Chen, SM. (eds) Social Networks: A Framework of Computational Intelligence. Studies in Computational Intelligence, vol 526. Springer, Cham. https://doi.org/10.1007/978-3-319-02993-1_13
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DOI: https://doi.org/10.1007/978-3-319-02993-1_13
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