Similarity Measures and Weighted Fuzzy C-Mean Clustering Algorithm
Authors: Bainian Li, Kongsheng Zhang, Jian Xu
Abstract:
In this paper we study the fuzzy c-mean clustering algorithm combined with principal components method. Demonstratively analysis indicate that the new clustering method is well rather than some clustering algorithms. We also consider the validity of clustering method.
Keywords: FCM algorithm, Principal Components Analysis, Clustervalidity
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1330571
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1727References:
[1] V.V. Cross and T.A. Sudkamp, Similarity and Compatibility in Fuzzy Set
Theory: assessment and Applications, Physica-Verlag, New York, 2002.
[2] M. Kalina, Derivatives of fuzzy functions and fuzzy derivatives, Tatra
Mountains Mathematical Publications 12 (1997) 27-34.
[3] K.L.Wu and M.S.Yang. Alternative c-means clustering algorithms. Pattern
Recognition. 2001,120:249-254.
[4] I.Berget, B.H.Mevi and T.Nas. New modifications and applications of
fuzzy c-means methodology. Computational Statistics & Data Analysis.
2008,52:2403-2418.
[5] X.Z.Wang, Y.D.Wang and L.J.Wang. Improving fuzzy c-means clustering
based on feature-weighted learning. Pattern Recognition Letters.2004,
25:1123-1132.
[6] K.S.Zhang, B.N.Li. New modification of fuzzy c-means clustering algorithm.
In Cao BY, Zhang CY Proceedings of the Third Annual Conference
on Fuzzy Information and Engineering .New York: Springer, 2009: 448-
455.
[7] W.L.Hung, M.S.Yang and D.H.Chen. Bootstrapping approach to featureweight
selection in fuzzy c-means algorithms with an application in color
image segmentation. Pattern Recognition Letters,2008,29:1317-1325.
[8] J.J.Higgings. Introduction to Modern Nonparametric Statistics. Duxbury,
Belmont, CA,2002.
[9] K.J.Zhu, S.H.Shu and J.L. Li. Optimal number of clusters and the best
partion in fuzzy c-means. Systems, Engineering-Theory and Practice.
2005, 3:52-61.(in Chinese)
[10] Y.J.Zhang, W.N.Wang, X.N. Zhang and Y.Li. A cluster validity index
for fuzzy clustering. Information Sciences. 2008,178:1205-1218.