Abstract
While analyzing the previous methods for determining the number of probability-based clustering, this paper introduces an improved Monte Carlo Cross-Validation algorithm (iMCCV) and attempts to solve the posterior probabilities spread problem, which cannot be resolved by the Monte Carlo Cross-Validation algorithm. Furthermore, we present a hybrid approach to determine the number of probability-based clustering by combining the iMCCV algorithm and the parallel coordinates visual technology. The efficiency of our approach is discussed with experimental results.
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© 2004 Springer-Verlag Berlin Heidelberg
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Dai, T., Li, C., Sun, J. (2004). Determining the Number of Probability-Based Clustering: A Hybrid Approach. In: Chi, CH., Lam, KY. (eds) Content Computing. AWCC 2004. Lecture Notes in Computer Science, vol 3309. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30483-8_51
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DOI: https://doi.org/10.1007/978-3-540-30483-8_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23898-0
Online ISBN: 978-3-540-30483-8
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