An Improved Fuzzy c-Means Clustering Algorithm Based on Shadowed Sets and PSO

To organize the wide variety of data sets automatically and acquire accurate classification, this paper presents a modified fuzzy c-means algorithm (SP-FCM) based on particle swarm optimization (PSO) and shadowed sets to perform feature clustering. SP-FCM introduces the global search property of PSO to deal with the problem of premature convergence of conventional fuzzy clustering, utilizes vagueness balance property of shadowed sets to handle overlapping among clusters, and models uncertainty in class boundaries. This new method uses Xie-Beni index as cluster validity and automatically finds the optimal cluster number within a specific range with cluster partitions that provide compact and well-separated clusters. Experiments show that the proposed approach significantly improves the clustering effect.

[1]  Gerardo Beni,et al.  A Validity Measure for Fuzzy Clustering , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Thomas A. Runkler,et al.  Fuzzy Clustering by Particle Swarm Optimization , 2006, 2006 IEEE International Conference on Fuzzy Systems.

[3]  Richard Weber,et al.  Dynamic clustering with soft computing , 2012, WIREs Data Mining Knowl. Discov..

[4]  James C. Bezdek,et al.  Some new indexes of cluster validity , 1998, IEEE Trans. Syst. Man Cybern. Part B.

[5]  James M. Keller,et al.  Comparing Fuzzy, Probabilistic, and Possibilistic Partitions , 2010, IEEE Transactions on Fuzzy Systems.

[6]  Donald W. Bouldin,et al.  A Cluster Separation Measure , 1979, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  James M. Keller,et al.  Fuzzy Models and Algorithms for Pattern Recognition and Image Processing , 1999 .

[8]  Hans-Peter Kriegel,et al.  Clustering high-dimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering , 2009, TKDD.

[9]  Witold Pedrycz,et al.  Shadowed sets in the characterization of rough-fuzzy clustering , 2011, Pattern Recognit..

[10]  Witold Pedrycz,et al.  Shadowed sets: representing and processing fuzzy sets , 1998, IEEE Trans. Syst. Man Cybern. Part B.

[11]  Ujjwal Maulik,et al.  Validity index for crisp and fuzzy clusters , 2004, Pattern Recognit..

[12]  Suresh Chandra Satapathy,et al.  Data Clustering Using Modified Fuzzy-PSO (MFPSO) , 2011, MIWAI.

[13]  Pradipta Maji,et al.  Robust Rough-Fuzzy C-Means Algorithm: Design and Applications in Coding and Non-coding RNA Expression Data Clustering , 2013, Fundam. Informaticae.

[14]  Chia-Feng Juang,et al.  Hierarchical Cluster-Based Multispecies Particle-Swarm Optimization for Fuzzy-System Optimization , 2010, IEEE Transactions on Fuzzy Systems.

[15]  James M. Keller,et al.  The possibilistic C-means algorithm: insights and recommendations , 1996, IEEE Trans. Fuzzy Syst..

[16]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[17]  Witold Pedrycz,et al.  Shadowed c-means: Integrating fuzzy and rough clustering , 2010, Pattern Recognit..

[18]  P. V. G. D. Prasad Reddy,et al.  Performance Comparisons of PSO based Clustering , 2010, ArXiv.

[19]  Anil K. Jain.  Data clustering: 50 years beyond K-means , 2008, Pattern Recognit. Lett..

[20]  Ajith Abraham,et al.  Fuzzy C-means and fuzzy swarm for fuzzy clustering problem , 2011, Expert Syst. Appl..

[21]  James C. Bezdek,et al.  Fuzzy mathematics in pattern classification , 1973 .

[22]  Oscar Castillo,et al.  A review on type-2 fuzzy logic applications in clustering, classification and pattern recognition , 2014, Appl. Soft Comput..

[23]  Hung T. Nguyen,et al.  Data Clustering Using Variants of Rapid Centroid Estimation , 2014, IEEE Transactions on Evolutionary Computation.

[24]  Thomas A. Runkler.  Ant colony optimization of clustering models , 2005, Int. J. Intell. Syst..

[25]  Shokri Z. Selim,et al.  A global algorithm for the fuzzy clustering problem , 1993, Pattern Recognit..

[26]  Witold Pedrycz,et al.  From fuzzy sets to shadowed sets: Interpretation and computing , 2009, Int. J. Intell. Syst..

[27]  James C. Bezdek,et al.  Optimization of fuzzy clustering criteria using genetic algorithms , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[28]  Fenglou Mao,et al.  Parallel Clustering Algorithm for Large Data Sets with Applications in Bioinformatics , 2009, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[29]  Thomas A. Runkler.  Ant colony optimization of clustering models: Research Articles , 2005 .