JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2016, Vol. 51 ›› Issue (5): 102-105.doi: 10.6040/j.issn.1671-9352.3.2015.105

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The fuzzy clustering algorithm based on inclusion index of Gausian membership function

ZHAI Peng1,2, LI Deng-dao3   

  1. 1. Department of Computer Science, University of Jining, Qufu 273155, Shandong, China;
    2. State Key Laboratory of Digital Publishing Technology(Peking University Founder Group Co., Ltd), Beijing 100871, China;
    3. College of Information Science and Engineering, Shandong University of Science and Technolgy, Qingdao 266590, Shandong, China
  • Received:2015-08-02 Online:2016-05-20 Published:2016-05-16

Abstract: Based on traditional fuzzy clustering algorithm, such as Fuzzy algorithm and C-means algorithm, the definition of inclusion index is taken into account the fuzzy clustering algorithm proposed, which is based on Gaussian membership functions. This algorithm ensure that the distance of each classification to another classifications is the same by a semi definite matrix, which preserves the inclusion index of Gausian membership function. The simulation experiment results with the Wine data set of UCI show that, compared with FCM, FIC algorithm has more effectiveness and feasibility.

Key words: clustering algorithm, distance, membership function, inclusion index

CLC Number: 

  • TP311
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