Entropy and Correlation: Some Comments 论文
1987IEEE Transactions on Systems Man and Cybernetics引用 254
Neural Networks and Applications
摘要
For measuring the degree of association or correlation between two nominal variables, a measure based on informational entropy is presented as being preferable to that proposed recently by Horibe [1]. Asymptotic developments are also presented that may be used for making approximate statistical inferences about the population measure when the sample size is reasonably large. The use of this methodology is illustrated using a numerical example.