As the field of data analysis grows rapidly due to the large amounts of data being generated, effective data classification has become increasingly important. This paper introduces the RUle Mutation Classifier (RUMC), which represents a significant improvement over the Rule Aggregation ClassifiER (RACER). RUMC uses innovative rule mutation techniques based on evolutionary methods to improve classification accuracy. In tests with forty datasets from OpenML and the UCI Machine Learning Repository, RUMC consistently outperformed twenty other well-known classifiers, demonstrating its ability to uncover valuable insights from complex data.

翻译：随着数据生成量的急剧增加，数据分析领域迅速发展，有效的数据分类变得日益重要。本文介绍了规则突变分类器（RUMC），该模型相较于规则聚合分类器（RACER）实现了显著改进。RUMC采用基于进化方法的创新规则突变技术，以提高分类准确性。在来自OpenML和UCI机器学习知识库的四十个数据集测试中，RUMC始终优于其他二十种知名分类器，证明了其从复杂数据中挖掘有价值洞见的能力。