Abstract
The mean shift clustering algorithm is a useful tool for clustering numeric data. Recently, Chang-Chien et al. [1] proposed a mean shift clustering algorithm for circular data that are directional data on a plane. In this paper, we extend the mean shift clustering for directional data on a hypersphere.The three types of mean shift procedures are considered. With the proposed mean shift clustering for the data on a hypersphere it is not necessary to give the number of clusters since it can automatically find a final cluster number with good clustering centers. Several numerical examples are used to demonstrate its effectiveness and superiority of the proposed method.
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Yang, MS., Chang-Chien, SJ., Kuo, HC. (2014). On Mean Shift Clustering for Directional Data on a Hypersphere. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2014. Lecture Notes in Computer Science(), vol 8468. Springer, Cham. https://doi.org/10.1007/978-3-319-07176-3_70
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DOI: https://doi.org/10.1007/978-3-319-07176-3_70
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07175-6
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