Abstract
Clustering is the most important task in unsupervised learning and clustering validity is a major issue in cluster analysis. In this paper, a new strategy called Clustering Algorithm Based on Histogram Threshold (HTCA) is proposed to improve the execution time. The HTCA method combines a hierarchical clustering method and Otsu’s method. Compared with traditional clustering algorithm, our proposed method would save at leastten several times of execution time without losing the accuracy. From the experiments, we find that the performance with regard to speed up the execution time of the HTCA is much better than traditional methods.
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Shieh, SL., Lin, TC., Szu, YC. (2012). An Efficient Clustering Algorithm Based on Histogram Threshold. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Intelligent Information and Database Systems. ACIIDS 2012. Lecture Notes in Computer Science(), vol 7197. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28490-8_4
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DOI: https://doi.org/10.1007/978-3-642-28490-8_4
Publisher Name: Springer, Berlin, Heidelberg
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