Abstract
K-means is a classic, the division of the clustering algorithm, apply to the classification of the globular data. According to the initial clustering center, this paper comprehensive consideration the characteristics of various Hierarchical cluster algorithms and choose the appropriate Hierarchical cluster algorithm to improve K-means, and combined with Hainan Green Tangerine Peel cluster analysis of data which is compared experiments. The results indicate that the improved algorithm have increasing the distance between classes with each others, get a stable of cluster results and better implementation data mining. Finally to summary the two algorithms and the further research direction.
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© 2014 IFIP International Federation for Information Processing
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Luo, Y., Fu, H. (2014). Modified K-means Algorithm for Clustering Analysis of Hainan Green Tangerine Peel. In: Li, H., Mäntymäki, M., Zhang, X. (eds) Digital Services and Information Intelligence. I3E 2014. IFIP Advances in Information and Communication Technology, vol 445. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45526-5_14
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DOI: https://doi.org/10.1007/978-3-662-45526-5_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-45525-8
Online ISBN: 978-3-662-45526-5
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