摘要
本文根据信息熵概念,提出了反映类别划分不确定性的聚类有效性评价指标,该指标为正确地确定实验数据的聚类数提供了依据.通过例子说明了该指标的有效性.
A index of cluster effectiveness representing classification uncertainty is presented in this paper based on the concept of information entropy. This index provides a basis for determining categories number of experimental data. Finally, the effectiveness of the index is illustrated by an example.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
1997年第2期184-188,共5页
Pattern Recognition and Artificial Intelligence
关键词
模糊聚类
熵
评价
聚类分析
Fuzzy Cluster Analysis, Entropy, Evaluation
