University evaluation and ranking is an extremely complex activity. Major universities are struggling because of increasingly complex indicator systems of world university rankings. So can we find the meta-indicators of the index system by simplifying the complexity? This research discovered three meta-indicators based on interpretable machine learning. The first one is time, to be friends with time, and believe in the power of time, and accumulate historical deposits; the second one is space, to be friends with city, and grow together by co-develop; the third one is relationships, to be friends with alumni, and strive for more alumni donations without ceiling.
翻译：大学的评价和排名是一项极其复杂的活动。主要大学正因为世界大学排名指标系统日益复杂而挣扎。 因此,我们能否通过简化复杂性来找到指数系统的元指标?这项研究发现了三个基于可解释的机器学习的元指标。 第一个是时间,与时间保持朋友关系,相信时间的力量,积累历史存款;第二个是空间,与城市保持朋友关系,并通过共同开发共同成长;第三个是关系,与校友保持朋友关系,并争取更多的校友捐款而无上限。
相关内容
微信扫码咨询专知VIP会员