河北大学学报(自然科学版) ›› 2016, Vol. 36 ›› Issue (3): 225-228.DOI: 10.3969/j.issn.1000-1565.2016.03.001

• •    下一篇

基于宽松下近似的模糊决策树归纳算法

张群峰   

  • 收稿日期:2015-06-16 出版日期:2016-05-25 发布日期:2016-05-25
  • 作者简介:张群峰(1963-),男,河北邯郸人,河北大学副教授,主要从事机器学习及粗糙集理论研究. E-mail:zhangqunfeng@hbu.cn
  • 基金资助:
    河北省自然科学基金资助项目(F2015201185);保定市科学技术研究与发展计划指导项目(12ZS005;12ZS006)

A fuzzy decision tree induction algorithm based on loose lower approximation

ZHANG Qunfeng   

  1. College of Mathematics and Information Science, Hebei University, Baoding 071002, China
  • Received:2015-06-16 Online:2016-05-25 Published:2016-05-25

摘要: 利用模糊相似关系对连续型决策表进行模糊化,进而运用宽松下近似定义启发式作为选择扩展属性的标准,从模糊决策表学习模糊决策树.

关键词: 连续型决策表, 宽松下近似, 模糊决策树

Abstract: To induce a fuzzy decision tree from a continuous decision table,a method based on loose lower approximation in fuzzy rough set theory is proposed.First,a fuzzy decision table is generated by clustering fuzzy similarity relations.Second,based on loose lower approximation,a measure of the importance of a condition attribute is introduced.Finally,using this measure as a criterion for selecting the expanding attribute,a fuzzy decision tree induction algorithm is proposed and an illustrative example is provided.

Key words: continuous decision table, loose lower approximation, fuzzy decision tree

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