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The Kendall Rank Correlation between Intuitionistic Fuzzy Sets: An Extended Analysis

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Book cover Soft Computing: State of the Art Theory and Novel Applications

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 291))

Abstract

This paper is a continuation and extension of our previous works on correlation coefficients between Atanassov’s intuitionistic fuzzy sets (A-IFSs, for short), notably on the Pearson coefficient r and the Spearman correlation coefficient to measure the degree of association between A-IFSs. Here, we develop, and illustrate on examples, the concept of the Kendall rank correlation for A-IFSs which is another important measure of correlation.

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References

  1. Nelsen, R.B.: Kendall tau metric. In: Hazewinkel, M. (ed.) Encyclopedia of Mathematics. Springer (2001) ISBN 978-1556080104

    Google Scholar 

  2. Aczel, A.D.: Complete business statistics. Richard D. Irvin, Inc. (1998)

    Google Scholar 

  3. Atanassov, K.: Intuitionistic Fuzzy Sets. VII ITKR Session. Sofia (Centr. Sci.-Techn. Libr. of Bulg. Acad. of Sci., 1697/84) (1983) (in Bulgarian)

    Google Scholar 

  4. Atanassov, K.: Intuitionistic Fuzzy Sets: Theory and Applications. Springer (1999)

    Google Scholar 

  5. Barrett, P.M., McGowan, A.J., Page, V.: Dinosaur diversity and the rock record. Proc. Royal Society B 276, 2667–2674 (2009)

    Article  Google Scholar 

  6. Benson, R.B., Butler, R.J., Lindgren, J., Smith, A.S.: Mesozoic marine tetrapod diversity: mass extinctions and temporal heterogeneity in geological megabiases affecting vertebrates. Proc. Royal Society B 277, 829–834 (2010)

    Article  Google Scholar 

  7. Bracke, M., Edwards, S.A., Engel, B., Buist, W.G., Bo Algers, B.: Expert opinion as ’validation’ of risk assessment applied to calf welfare. Acta Veterinaria Scandinavica 50(29) (2008), doi:10.1186/1751-0147-50-29

    Google Scholar 

  8. Kurvers, R.H., Prins, H.H., van Wieren, S.E., van Oers, K., Nolet, B.A., Ronald, C., Ydenberg, R.C.: The effect of personality on social foraging: shy barnacle geese scrounge more. Proc. Royal Society B 277, 601–608 (2010)

    Article  Google Scholar 

  9. Griffiths, D.: A Pragmatic Approach to Spearmans Rank Correlation Coefficient. Teaching Statistics 2, 10–13 (1980)

    Article  Google Scholar 

  10. Helgason, C.M., Jobe, T.H.: Perception based reasoning and fuzzy cardinality provide direct measures of causality sensitive to initial conditions in the individual patient. International Journal of Computational Cognition 1, 79–104 (2003)

    Google Scholar 

  11. Helgason, C.M., Watkins, F.A., Jobe, T.H.: Measurable differences between sequential and parallel diagnostic decision processes for determining stroke subtype: A representation of interacting pathologies. Thromb. Haemost. 88, 210–212 (2002)

    Google Scholar 

  12. Henrysson, S.: Gathering, analyzing, and using data on test items. In: Thorndike, R.L. (ed.) Educational Measurement, pp. 130–159. American Council on Education, Washington D.C (1971)

    Google Scholar 

  13. Kendler, K.S., Parnas, J.: Philosophical Issues in Psychiatry: Explanation, Phenomenology, and Nosology. Johns Hopkins University Press (2008)

    Google Scholar 

  14. Kendall, M.G.: Rank correlation methods, 4th edn. Charles Griffin & Co., London (1970)

    MATH  Google Scholar 

  15. Moller, A.P., Alatalo, R.V.: Good-genes effects in sexual selection. Proc. Royal Society Lond. B 266, 85–91 (1999)

    Article  Google Scholar 

  16. Myers, J.L., Well, A.W.: Research Design and Statistical Analysis, 2nd edn. Lawrence Erlbaum (2003)

    Google Scholar 

  17. Noether, G.: Why Kendall Tau? Teaching Statistics 3(2), 41–43 (1981)

    Article  MathSciNet  Google Scholar 

  18. Rodgers, J.L., Nicewander, W.A.: Thirteen Ways to Look at the Correlation Coefficient. The American Statistician 42(1), 59–66 (1988)

    Article  Google Scholar 

  19. Szmidt, E., Baldwin, J.: Intuitionistic Fuzzy Set Functions, Mass Assignment Theory, Possibility Theory and Histograms. In: 2006 IEEE World Congress on Computational Intelligence, pp. 237–243 (2006)

    Google Scholar 

  20. Szmidt, E., Kacprzyk, J.: Remarks on some applications of intuitionistic fuzzy sets in decision making. Notes on IFS 2(3), 22–31 (1996c)

    MathSciNet  MATH  Google Scholar 

  21. Szmidt, E., Kacprzyk, J.: On measuring distances between intuitionistic fuzzy sets. Notes on IFS 3(4), 1–13 (1997)

    MathSciNet  MATH  Google Scholar 

  22. Szmidt, E., Kacprzyk, J.: Group Decision Making under Intuitionistic Fuzzy Preference Relations. In: IPMU 1998, pp. 172–178 (1998)

    Google Scholar 

  23. Szmidt, E., Kacprzyk, J.: Distances between intuitionistic fuzzy sets. Fuzzy Sets and Systems 114(3), 505–518 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  24. Szmidt, E., Kacprzyk, J.: On Measures on Consensus Under Intuitionistic Fuzzy Relations. In: IPMU 2000, pp. 1454–1461 (2000)

    Google Scholar 

  25. Szmidt, E., Kacprzyk, J.: Entropy for intuitionistic fuzzy sets. Fuzzy Sets and Systems 118(3), 467–477 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  26. Szmidt, E., Kacprzyk, J.: Analysis of Consensus under Intuitionistic Fuzzy Preferences. In: Proc. Int. Conf. in Fuzzy Logic and Technology, pp. 79–82. De Montfort Univ., Leicester (2001)

    Google Scholar 

  27. Szmidt, E., Kacprzyk, J.: Analysis of Agreement in a Group of Experts via Distances Between Intuitionistic Fuzzy Preferences. In: Proc. 9th Int. Conf. IPMU 2002, pp. 1859–1865 (2002a)

    Google Scholar 

  28. Szmidt, E., Kacprzyk, J.: An Intuitionistic Fuzzy Set Based Approach to Intelligent Data Analysis (an application to medical diagnosis). In: Abraham, A., Jain, L., Kacprzyk, J. (eds.) Recent Advances in Intelligent Paradigms and Applications, pp. 57–70. Springer (2002b)

    Google Scholar 

  29. Szmidt, E., Kacprzyk, J.: An Intuitionistic Fuzzy Set Based Approach to Intelligent Data Analysis (an application to medical diagnosis). In: Abraham, A., Jain, L., Kacprzyk, J. (eds.) Recent Advances in Intelligent Paradigms and Applications, pp. 57–70. Springer (2002c)

    Google Scholar 

  30. Szmidt, E., Kacprzyk, J.: Distances Between Intuitionistic Fuzzy Sets: Straightforward Approaches may not work. In: IEEE IS 2006, pp. 716–721 (2006)

    Google Scholar 

  31. Szmidt, E., Kacprzyk, J.: An Application of Intuitionistic Fuzzy Set Similarity Measures to a Multi-criteria Decision Making Problem. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds.) ICAISC 2006. LNCS (LNAI), vol. 4029, pp. 314–323. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  32. Szmidt, E., Kacprzyk, J.: Some Problems with Entropy Measures for the Atanassov Intuitionistic Fuzzy Sets. In: Masulli, F., Mitra, S., Pasi, G. (eds.) WILF 2007. LNCS (LNAI), vol. 4578, pp. 291–297. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  33. Szmidt, E., Kacprzyk, J.: A New Similarity Measure for Intuitionistic Fuzzy Sets: Straightforward Approaches not work. In: 2007 IEEE Conf. on Fuzzy Systems, pp. 481–486 (2007a)

    Google Scholar 

  34. Szmidt, E., Kacprzyk, J.: A new approach to ranking alternatives expressed via intuitionistic fuzzy sets. In: Ruan, D., et al. (eds.) Computational Intelligence in Decision and Control, pp. 265–270. World Scientific (2008)

    Google Scholar 

  35. Szmidt, E., Kacprzyk, J.: Amount of Information and Its Reliability in the Ranking of Atanassov’s Intuitionistic Fuzzy Alternatives. In: Rakus-Andersson, E., Yager, R.R., Ichalkaranje, N., Jain, L.C. (eds.) Recent Advances in Decision Making. SCI, vol. 222, pp. 7–19. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  36. Szmidt, E., Kacprzyk, J.: Ranking of Intuitionistic Fuzzy Alternatives in a Multi-criteria Decision Making Problem. In: Proceedings of the Conference: NAFIPS 2009, Cincinnati, USA, June 14-17, pp. 978–971. IEEE (2009) ISBN: 978-1-4244-4577-6

    Google Scholar 

  37. Szmidt, E., Kacprzyk, J.: Correlation of Intuitionistic Fuzzy Sets. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds.) IPMU 2010. LNCS (LNAI), vol. 6178, pp. 169–177. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  38. Szmidt, E., Kacprzyk, J.: The Spearman rank correlation coefficient between intuitionistic fuzzy sets. In: 2010 IEEE Int. Conf. on Intelligent Systems (IEEE IS 2010), London, pp. 276–280 (2010)

    Google Scholar 

  39. Szmidt, E., Kacprzyk, J.: The Kendall Rank Correlation between Intuitionistic Fuzzy Sets. In: Proc. World Conference on Soft Computing, San Francisco, CA, USA, May 23-26 (2011)

    Google Scholar 

  40. Szmidt, E., Kukier, M.: Classification of Imbalanced and Overlapping Classes using Intuitionistic Fuzzy Sets. In: IEEE IS 2006, London, pp. 722–727 (2006)

    Google Scholar 

  41. Szmidt, E., Kukier, M.: A New Approach to Classification of Imbalanced Classes via Atanassov’s Intuitionistic Fuzzy Sets. In: Wang, H.-F. (ed.) Intelligent Data Analysis: Developing New Methodologies Through Pattern Discovery and Recovery, pp. 85–101. Idea Group (2008)

    Google Scholar 

  42. Zadeh, L.A.: Fuzzy sets. Information and Control 8, 338–353 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  43. Zadeh, L.A.: Toward a perception-based theory of probabilistic reasoning with imprecise probabilities. Journal of Statistical Planning and Inference 105, 233–264 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  44. Zadeh, L.A.: Generalized theory of uncertainty (GTU) principal concepts and ideas. Computational Statistics and Data Analysis 51, 15–46 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  45. Zeng, W., Li, H.: Correlation coefficient of intuitionistic fuzzy sets. Journal of Industrial Engineering International 3(5), 33–40 (2007)

    Google Scholar 

  46. http://archive.ics.uci.edu/ml/datasets/Iris

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Szmidt, E., Kacprzyk, J., Bujnowski, P. (2013). The Kendall Rank Correlation between Intuitionistic Fuzzy Sets: An Extended Analysis. In: Yager, R., Abbasov, A., Reformat, M., Shahbazova, S. (eds) Soft Computing: State of the Art Theory and Novel Applications. Studies in Fuzziness and Soft Computing, vol 291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34922-5_4

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  • DOI: https://doi.org/10.1007/978-3-642-34922-5_4

  • Publisher Name: Springer, Berlin, Heidelberg

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