Abstract
This paper proposes a new method based on Dempster-Shafer (DS) evidence theory and Gaussian Mixture Modeling (GMM) technique to combine the cluster results from single clustering methods. We introduce the GMM technique to determine the confidence values for candidate results from each clustering method. Then we employ the DS theory to combine the evidences supplied by different clustering methods, based on which the final result is obtained. We tested the proposed ensemble clustering method on several commonly used datasets. The experimental results confirm that our method is effective and promising.
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Wu, Y., Liu, X., Guo, L. (2014). A New Ensemble Clustering Method Based on Dempster-Shafer Evidence Theory and Gaussian Mixture Modeling. In: Loo, C.K., Yap, K.S., Wong, K.W., Teoh, A., Huang, K. (eds) Neural Information Processing. ICONIP 2014. Lecture Notes in Computer Science, vol 8835. Springer, Cham. https://doi.org/10.1007/978-3-319-12640-1_1
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DOI: https://doi.org/10.1007/978-3-319-12640-1_1
Publisher Name: Springer, Cham
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