The Matthews Correlation Coefficient (MCC) is one of the popular measurements for classification accuracy. It has been generally regarded as a balanced measure which can be used even if the classes are of very different sizes. The study of this paper finds that this is not true. MCC deteriorates seriously when the dataset in classification are imbalanced. Experiment results and analysis show that MCC is not suitable for classification accuracy measurement on imbalanced datasets.

中文翻译：

---

不平衡数据集的Matthews相关系数（MCC）的性能

Matthews相关系数（MCC）是用于分类准确性的流行度量之一。通常认为它是一种平衡措施，即使类别的大小差异很大，也可以使用。本文的研究发现这是不正确的。当分类中的数据集不平衡时，MCC会严重恶化。实验结果和分析表明，MCC不适合在不平衡数据集上进行分类精度测量。