Computer Science ›› 2016, Vol. 43 ›› Issue (1): 61-63.doi: 10.11896/j.issn.1002-137X.2016.01.014

Previous Articles     Next Articles

Measuring Consistency of Two Datasets Using Shannon Entropy

CHE Xiao-ya and MI Ju-sheng   

  • Online:2018-12-01 Published:2018-12-01

Abstract: The basic idea of rough set theory is based on an indiscernibility relation,and through a pair of approximate operators,it can approximatively represent a given concept.It is used in the study of a data set for classification consistency to another data set.This paper presented a new approach to measure consistency degree of two datasets,and defined classification consistency by Shannon entropy.Taking the influence of neighborhood relations of different data into account,a general consistency measure was defined by introducing the expert knowledge into a fuzzy inference system,then we constructed a consistent generalized metric.Moreover,this method can prevent the “ black box ” phenomenon encountered in many modeling techniques and produce robust and interpretable results.

Key words: Consistency degree,Indiscernibility relation,Fuzzy partition,Shannon entrop

[1] Agresti A,Finlay B.Statistical Methods for the Social Sciences(third edition)[M].Prentice Hall,New Jersey,1997
[2] Chen C B,Wang L Y.Rough set-based clusing with refinement using Shannon’s entropy theory[J].Computer,Mathematics with Applications,2006,52(10/11):1563-1576
[3] Dubois D,Prade H,Yager R R.Fuzzy Information Engineering:A Guide Tour of Application[M].Wiley,New York,1997
[4] Hollins M,Faldowski R,Rao S,et al.Perceptual dimensions of tactile surface texture:a multidimensional scaling analysis[J].Perception and Psychophys,1997,54 (6):697-705
[5] Jolliffe I T.Principal Component Analysis(2rd edition)[M].Information Publishier Science,New York,2002
[6] Le Dien S.Hierarchical multiple factoranalysis:application tothe comparison of sensory profiles[J].Food Quality Preference,2003,14(5/6):397-403
[7] Pawlak Z.Rough sets[J].International Journal Computer and Information Sciences,1982,11(5):341-356
[8] Pawlak Z.Rough set theory and its applications in data analysis[J].Cybernet System,1998,29(7):661-688
[9] Polkowski L,Skowron A.Rough mereology and analytical morphology:new developments in rough set Theory[C]∥ De Glass M,Pawlak Z.eds.Proceedings of WOCFAI-95,Second World Conference on Fundamntals of Artificial Intelligence.Angkor,Paris,1995:343-354
[10] Qian Y H,Liang J Y,Dang C Y.Consistency measure,inclusion degree and fuzzy measure in decision tables[J].Fuzzy Sets and Systems,2008,159(18):2353-2377
[11] Tripathy B C,Ray G C.On mixed fuzzy to pological spaces and countability[J].Soft Computing,2012,16(10):1691-1695
[12] Weisgerg S.Applied Linear Regression(third edition)[M].John & Sons,New York,2005
[13] Xue Z,Zeng X,Koehl L,et al.Measuring consistency of twodatasets using fuzzy techniques and the concept of indiscerni-bility[J].Engineering Applications of Artificial Intelligence,2014,36:54-63
[14] Yao Y Q,Mi J S.Hybrid Monotonic Measure on Intutionistic Fuzzy Sets[J].Computer Science,2010,37(1):255-257(in Chinese)姚燕青,米据生.直觉模糊集上的混合单调包含度[J].计算机科学,2010,37(1):255-257

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!