Abstract
Clustering of incomplete data using a neural network and the Gradient-Based Fuzzy c-Means (GBFCM) is proposed in this paper. The proposed algorithm is applied to the Iris data to evaluate its performance. When compared with the existing Optimal Completion Strategy FCM (OCSFCM), the proposed algorithm shows 18%-20% improvement of performance over the OCSFCM.
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© 2005 Springer-Verlag Berlin Heidelberg
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Park, DC. (2005). Gradient-Based FCM and a Neural Network for Clustering of Incomplete Data. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539087_166
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DOI: https://doi.org/10.1007/11539087_166
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28323-2
Online ISBN: 978-3-540-31853-8
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