On Hesitant Fuzzy Clustering and Clustering of Hesitant Fuzzy Data

Since the notion of hesitant fuzzy set was introduced, some clustering algorithms have been proposed to cluster hesitant fuzzy data. Beside of hesitation in data, there is some hesitation in the clustering (classification) of a crisp data set. This hesitation may be arise in the selection process of a suitable clustering (classification) algorithm and initial parametrization of a clustering (classification) algorithm. Hesitant fuzzy set theory is a suitable tool to deal with this kind of problems. In this study, we introduce two different points of view to apply hesitant fuzzy sets in the data mining tasks, specially in the clustering algorithms.

[1]  Zeshui Xu.  Intuitionistic Fuzzy Aggregation Techniques , 2012 .

[2]  Jiawei Han,et al.  Data Mining: Concepts and Techniques , 2000 .

[3]  Zeshui Xu,et al.  Distance and similarity measures for hesitant fuzzy sets , 2011, Inf. Sci..

[4]  Hans-Peter Kriegel,et al.  Density-Connected Sets and their Application for Trend Detection in Spatial Databases , 1997, KDD.

[5]  Francisco Herrera,et al.  Hesitant Fuzzy Sets: State of the Art and Future Directions , 2014, Int. J. Intell. Syst..

[6]  Zeshui Xu,et al.  Hesitant fuzzy agglomerative hierarchical clustering algorithms , 2015, Int. J. Syst. Sci..

[7]  Yanhui Guo,et al.  NECM: Neutrosophic evidential c-means clustering algorithm , 2014, Neural Computing and Applications.

[8]  Peter J. Rousseeuw,et al.  Finding Groups in Data: An Introduction to Cluster Analysis , 1990 .

[9]  Atefeh Taghavi,et al.  An introduction to hesitant fuzzy data clustering , 2015, 2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS).

[10]  Krassimir T. Atanassov,et al.  Intuitionistic fuzzy sets , 1986 .

[11]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[12]  Anil K. Jain.  Data clustering: 50 years beyond K-means , 2010, Pattern Recognit. Lett..

[13]  Zeshui Xu.  Intuitionistic Fuzzy Aggregation and Clustering , 2012, Studies in Fuzziness and Soft Computing.

[14]  Na Chen,et al.  Correlation coefficients of hesitant fuzzy sets and their applications to clustering analysis , 2013 .

[15]  Rafal Scherer,et al.  Multiple Fuzzy Classification Systems , 2012, Studies in Fuzziness and Soft Computing.

[16]  Esfandiar Eslami,et al.  A Definition for Hesitant fuzzy Partitions , 2016, Int. J. Comput. Intell. Syst..

[17]  Esfandiar Eslami,et al.  GHFHC: Generalized Hesitant Fuzzy Hierarchical Clustering Algorithm , 2016, Int. J. Intell. Syst..

[18]  V. Torra,et al.  A framework for linguistic logic programming , 2010 .

[19]  Abdol Hamid Pilevar,et al.  GCHL: A grid-clustering algorithm for high-dimensional very large spatial data bases , 2005, Pattern Recognit. Lett..

[20]  Sadaaki Miyamoto,et al.  A definition for I-fuzzy partitions , 2011, Soft Comput..

[21]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[22]  M. Sato,et al.  Fuzzy clustering model for fuzzy data , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[23]  Hai Wang,et al.  Generalized hesitant fuzzy sets and their application in decision support system , 2013, Knowl. Based Syst..

[24]  Miin-Shen Yang,et al.  A robust EM clustering algorithm for Gaussian mixture models , 2012, Pattern Recognit..

[25]  Tamalika Chaira,et al.  A novel intuitionistic fuzzy C means clustering algorithm and its application to medical images , 2011, Appl. Soft Comput..

[26]  Na Chen,et al.  Hierarchical hesitant fuzzy K-means clustering algorithm , 2014, Applied Mathematics-A Journal of Chinese Universities.

[27]  Witold Pedrycz,et al.  Advances in Fuzzy Clustering and its Applications , 2007 .

[28]  Humberto Bustince,et al.  Aggregation functions for typical hesitant fuzzy elements and the action of automorphisms , 2014, Inf. Sci..

[29]  Zeshui Xu,et al.  Hesitant fuzzy information aggregation in decision making , 2011, Int. J. Approx. Reason..