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A Study on Data Clustering Method Using Local Probability

국부 확률을 이용한 데이터 분류에 관한 연구

  • 손창호 (삼창기업(주)) ;
  • 최원호 (울산대학교 전기전자정보시스템공학부) ;
  • 이재국 (울산대학교 전기전자정보시스템공학부)
  • Published : 2007.01.01

Abstract

In this paper, we propose a new data clustering method using local probability and hypothesis theory. To cluster the test data set we analyze the local area of the test data set using local probability distribution and decide the candidate class of the data set using mean standard deviation and variance etc. To decide each class of the test data, statistical hypothesis theory is applied to the decided candidate class of the test data set. For evaluating, the proposed classification method is compared to the conventional fuzzy c-mean method, k-means algorithm and Discriminator analysis algorithm. The simulation results show more accuracy than results of fuzzy c-mean method, k-means algorithm and Discriminator analysis algorithm.

Keywords

References

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