References

Al-Zoubi, M.D.B., A.D. Ali and A.A. Yahya, 2008. Fuzzy clustering-based approach for outlier detection. Proceedings of the 9th WSEAS International Conference on Applications of Computer Engineering, March 23-25, 2010, Penang, Malaysia, pp: 192-197.

Angiulli, F., S. Basta and C. Pizzuti, 2006. Distance-based detection and prediction of outliers. IEEE Trans. Knowl. Data Eng., 18: 145-160.
CrossRef  |  

Barnett, V. and T. Lewis, 1994. Outliers in Statistical Data. 3rd Edn., John Wiley and Sons, New York, ISBN: 0-471-93094-6, Pages: 584.

Bezdek, J., J.Keller and R. Krishnapuram, 1999. Fuzzy Models and Algorithms for Pattern Recognition and Image Processing. 1st Edn., Kluwer Academy Publishers, Norwell, MA., USA., ISBN: 0792385217, pp: 792.

Bezdek, J.C., 1981. Pattern Recognition with Fuzzy Objective Function Algoritms. 1st Edn., Plenum Press, New York, USA.

Blake, C., E. Keogh and C. Merz, 1998. UCI Repository of Machine Learning Database. University of California, Irvine, CA., USA.

Bouroumi, A., M. Limouri and A. Essaid, 2000. Unsupervised fuzzy learning and cluster seeking. Intell. Data Anal., 4: 241-253.
Direct Link  |  

Breunig, M.M., H.P. Kriegel, R.T. Ng and J. Sander, 2000. LOF: Identifying density-based local outliers. Proceedings of the International Conference on Management of Data, May 15-18, 2000, Dallas, TX., USA., pp: 93-104.

Cimino, M.G.C.A., G. Frosini, B. Lazzerini and F. Marcelloni, 2007. On the noise distance in robust fuzzy c-means. Int. J. Comput. Sci. Eng., Vol. 1.

Dave, R.N. and R. Krishnapuram, 1997. Robust clustering methods. A unified view. IEEE Trans. Fuzzy Syst., 5: 270-293.
Direct Link  |  

Dave, R.N. and S. Sen, 1997. Noise clustering algorithm revisited. Proceedings of the Annual Meeting of the North American Fuzzy Information Processing Society, September 21-24, 1997, Syracuse, NY., USA., pp: 199-204.

Dave, R.N., 1991. Characterization and detection of noise in clustering. Pattern Recogn. Lett., 12: 657-664.
CrossRef  |  

Han, J. and M. Kamber, 2006. Data Mining: Concepts and Techniques. 2nd Edn., Morgan Kaufmann Publisher, San Fransisco, USA., ISBN-13: 978-1558609013, Pages: 800.

Hathaway, R.J. and J.C. Bezdek, 2001. Fuzzy c-means clustering of incomplete data. IEEE Trans. Syst. Man Cybernet. B: Cybernet., 31: 735-744.
CrossRef  |  

Hawkins, D.M., 1980. Identifications of Outliers. Chapman and Hall, London, UK., ISBN-13: 9780412219009.

Jain, A.K., 2010. Data clustering: 50 years beyond K-means. Pattern Recogn. Lett., 31: 651-666.
CrossRef  |  Direct Link  |  

Jolion, J.M. and A. Rosenfeld, 1989. Cluster detection in background noise. Pattern Recogn., 22: 603-607.
CrossRef  |  

Knorr, E.M. and R.T. Ng, 1998. Algorithms for mining distance-based outliers in large dataset. Proceedings of the 24rd International Conference on Very Large Data Bases, August 24-27, 1998, San Francisco, CA., USA., pp: 392-403.

Krishnapuram, R. and J.M. Keller, 1993. A possibilistic approach to clustering. IEEE Trans. Fuzzy Syst., 1: 98-110.

Loureiro, A., L. Torgo and C. Soares, 2004. Outlier detection using clustering methods: A data cleaning application. Proceedings of KDNet Symposium on Knowledge-Based Systems for the Public Sector, June 3-4, 2004, Bonn, Germany -.

Ohashi, Y., 1984. Fuzzy clustering and robust estimation. Proceedings of the 9th International SAS Users Group Meeting, March 18-21, 1984, Hollywood Beach, USA -.

Ramaswamy, S., R. Rastogi and K. Shim, 2000. Efficient algorithms for mining outliers from large data sets. Proceedings of the International Conference on Management of Data, May 15-18, 2000, Dallas, TX., USA., pp: 427-438.

Tang, C., S. Wang and Y. Chen, 2012. Clustering of steel strip sectional profiles based on robust adaptive fuzzy clustering algorithm. Comput. Inform., 30: 357-380.
Direct Link  |