Abstract
Clustering is a hot topic of data mining. After studying the existing classical algorithm of clustering, this paper proposes a new clustering algorithm based on probability, and makes a new definition for clustering and outlier. According to the distribution characteristics of sample data, this algorithm determines the initial clustering center automatically. It also implements eliminating outliers in the process of clustering. The experiment results on IRIS show that this algorithm can clustering effectively.
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Yue, Z., Chuansheng, Z. (2014). A New Clustering Algorithm Based on Probability. In: Pan, JS., Snasel, V., Corchado, E., Abraham, A., Wang, SL. (eds) Intelligent Data analysis and its Applications, Volume II. Advances in Intelligent Systems and Computing, vol 298. Springer, Cham. https://doi.org/10.1007/978-3-319-07773-4_12
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DOI: https://doi.org/10.1007/978-3-319-07773-4_12
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07772-7
Online ISBN: 978-3-319-07773-4
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