一、报告时间

2025年10月9日（星期四）19:00

二、报告形式

经济管理学院335会议室

腾讯会议号：708323993

三、报告人

安庆贤中南大学教授

四、报告主题

Data Envelopment Analysis Clustering: An optimization based machine learning

五、报告摘要

In a data-driven environment, clustering methods have become essential tools for grouping units into distinct groups and uncovering underlying feature structures within datasets. Most existing clustering methods analyze these features based on distance functions, and the cost-benefit relationship is not a focus. In this study, we approach clustering from the perspective of constructing a composite index reflecting the cost-benefit ratio. Among various aggregating methods, data envelopment analysis (DEA), as a nonparametric optimization technique, can provide a ratio index that incorporates both cost and benefit features, and effectively models cost-benefit relationships. Therefore, we develop an explainable clustering method based upon DEA. We term this method “k-DEA-weights” clustering because it adopts the k-means clustering framework and clusters units based on DEA-derived weights. Thus, it can be viewed as an optimization-based explainable machine learning technique.

六、报告人简介

安庆贤，教授，国家高层次青年拔尖人才，湖南省党代表。受聘为湖南股权交易所专家库专家、国际农发基金贷款湖南省乡村振兴发展项目“省经济技术咨询委员会”专家、国家重点研发计划“社会治理与智慧社会科技支撑”重点专项项目论证专家。现任中国管理科学与工程学会理事和青委会委员、湖南省系统工程与管理学会常务理事兼副秘书长。

长期从事数据包络分析、大数据分析与数据科学、资源与环境经济等领域研究，以第一或通讯作者在European Journal of Operational Research、管理科学学报等高水平期刊发表论文40余篇，其中中文顶刊2篇，ABS四星期刊论文9篇。主持国家自然科学基金项目3项、湖南省自科优秀青年基金项目，承担国家社科基金重大项目子课题1项等。研究成果获教育部高等学校科学研究优秀成果奖（人文社会科学）三等奖（排名1）、Elsevier 最佳论文奖（Best Paper Award of OMEGA）等。