计算机工程与应用 ›› 2010, Vol. 46 ›› Issue (36): 161-164.DOI: 10.3778/j.issn.1002-8331.2010.36.044
• 数据库、信号与信息处理 • 上一篇 下一篇
许昌林，魏立力
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XU Chang-lin，WEI Li-li
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摘要： 在区间值模糊集理论和Vague集理论的基础上，提出了一种新的基于Vague集相似度量的模糊分类方法，对Fisher建立的Iris数据库进行了分类实验处理，分类结果的正确率超过95%。该方法计算简单有效，具有一定的实际应用价值。
关键词: Vague集, 相似度量, 区间值模糊集, 模糊分类
Abstract: According to the interval-valued fuzzy set theory and the Vague sets theory，a new algorithm based on similarity measures between Vague sets is proposed and applied to the Iris data presented by Fisher.The result shows that more than 95% of the data are classified rightly.The method is simple and efficient，so it is useful for some real problems.
Key words: Vague sets, similarity measure, interval-valued fuzzy set, fuzzy classification
中图分类号:
TP18
许昌林，魏立力. 基于Vague集相似度量的模糊分类[J]. 计算机工程与应用, 2010, 46(36): 161-164.
XU Chang-lin，WEI Li-li. Fuzzy classification based on similarity measures between Vague sets[J]. Computer Engineering and Applications, 2010, 46(36): 161-164.
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http://cea.ceaj.org/CN/Y2010/V46/I36/161
