Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (20): 176-180.DOI: 10.3778/j.issn.1002-8331.2010.20.049

• 人工智能 • Previous Articles     Next Articles

Fuzzy classification algorithm based on fuzzy entropy

ZHAI Jun-hai1,WANG Hua-chao1,ZHANG Su-fang2   

  1. 1.Key Lab of Machine Learning and Computational Intelligence,College of Mathematics and Computer Science,Hebei University,Baoding,Hebei 071002,China
    2.Teaching and Research of Section of Mathematics,Hebei Information Engineering School,Baoding,Hebei 071000,China
  • Received:2010-04-14 Revised:2010-05-18 Online:2010-07-11 Published:2010-07-11
  • Contact: ZHAI Jun-hai



  1. 1.河北大学 数学与计算机学院,河北省机器学习与计算智能重点实验室,河北 保定 071002
    2.河北省信息工程学校 数学教研室,河北 保定 071000
  • 通讯作者: 翟俊海

Abstract: Fuzzy ID3 uses the fuzzy classification entropy as the criterion to select the expanded attributes,the fuzzy decision tree used for classification of data is recursively generated from top to bottom.Based on fuzzy entropy,this paper presents a fuzzy classification algorithm.Different from fuzzy ID3,the fuzzy entropies of fuzzy condition attributes are used as weights to weigh the relative fuzzy frequencies.The proposed algorithm integrates the contributions of all fuzzy condition attributes together.An illustrative example as well as the experimental results demonstrates the effectiveness of the proposed method.

Key words: fuzzy information system, fuzzy decision tree, fuzzy ID3, fuzzy entropy, fuzzy condition attributes, fuzzy decision attributes

摘要: 在模糊ID3算法中,用模糊分类熵选择扩展属性,以自顶向下的方式递归地构建模糊决策树,对数据进行分类。提出了一种基于属性模糊熵的模糊分类算法,不同于模糊ID3算法,模糊条件属性的模糊熵作为权值用来对相对模糊频率进行加权,综合考虑各个模糊条件属性对分类的贡献。实例分析和实验结果表明了这一算法的有效性。

关键词: 模糊信息系统, 模糊决策树, 模糊ID3算法, 模糊熵, 模糊条件属性, 模糊决策属性

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