Abstract: The common correlation coefficient reflects the linear or nonlinear degree between variables. Based on the Hilbert-Schmidt Independent Criterion（HSIC） for biased estimation（HSIC0）, a method of measuring the nonlinear correlation between classes based on class labels is proposed. Through six groups of real and different types of data sets, and linear kernels, polynomial kernels, RBF kernels and Sigmoid kernel functions are selected for experiments. The results show that the method has good feasibility.

Key words: correlation coefficient, HSIC0, kernel function, nonlinear correlation, class label

摘要： 常见的相关系数反映变量之间的线性或非线性程度。基于希尔伯特-斯密特独立准则（Hilbert-Schmidt Independence Criterion，HSIC）的有偏估计（HSIC0），提出了根据类标签划分出的类与类之间的非线性相关关系的度量方法。通过六组真实的、不同类型的数据集，分别选取了线性核、多项式核、RBF核和Sigmoid核函数进行实验。结果表明，该方法具有较好的可行性。

关键词: 相关系数, HSIC0, 核函数, 非线性, 类标签