摘要
在粗糙集理论中,基于度量决策表中属性重要性大小的需要,有学者提出了互补信息熵的概念。在此基础上,定义了条件熵和互信息等概念,并验证了三者之间的关系,即互补信息熵是条件熵与互信息的和;类似于互补信息熵,互信息同样具有单调性。
The concept of complementary information entropy based on the needs of the importance of attributes in measuring decision table is proposed in rough set theory. On this basis, condition entropy and mutual information are deifned and the relationship among the three is veriifed, i.e. the sum of condition entropy and mutual information is complementary information entropy; Mutual information also has the monotonicity similar to complementary information entropy.
出处
《文山学院学报》
2016年第3期42-44,共3页
Journal of Wenshan University
基金
云南省教育厅科研基金项目"基于粗糙集的数据挖掘算法研究"(2015Y470)
关键词
信息测度
互补信息熵
条件熵
互信息
information measure
complementary information entropy
conditional entropy
mutual information
