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1. 北方交通大学计算机学院,北京,100044
2. 北京大学数学科学院信息科学系,北京,100871
3. 北方交通大学计算机学院北京,100044
4. 北京大学数学科学院信息科学系北京,100871
Published:2003
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YU Jian, CEHNG Qian-sheng. A Note on the Weighting Exponent m in FCM Algorithm[J]. Acta Electronica Sinica, 2003, 31(3): 478-480.
DOI:
YU Jian, CEHNG Qian-sheng. A Note on the Weighting Exponent m in FCM Algorithm[J]. Acta Electronica Sinica, 2003, 31(3): 478-480. DOI:
模糊c均值算法(FCM)是经常使用的聚类算法之一.使用模糊c均值算法时
如何选取模糊指标
m
一直是一个悬而未决的问题.部分文献根据实验结果建议最佳的权重指数可能位于区间
但大多数研究者使用
=2.本文阐述了FCM算法有效性与聚类有效性之间的理论联系
指出如果某个权重指数使得FCM算法作为聚类算法不能有效工作
则其不能作为最佳的权重指数.据此
我们进行了数据实验
数据实验结果说明了权重指数的最佳取值未必位于区间 .
The fuzzy c-means algorithm (FCM) is one of widely used clustering algorithms.It is an open problem how to select an appropriate fuzziness index
when implementing the FCM.Some researchers have suggested that the best choice for
is probably in the interval based on their experimental results.In this paper
we discovered the theoretical connection between the validity of FCM algorithm as clustering algorithm and clustering validity
and pointed out that the weighting exponent
is not the optimal if it makes the FCM not to work properly as a clustering algorithm.According to this analysis
we carried on one experiment.The experimental result shows that the optimal weighting exponent in FCM algorithm could not always belong to the range .
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