id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fcis-19452	Hu, Jiaxin; Zhang, Xinchen; Xiao, Shuangyue; Fan, Linli; Liu, Li; Li, Tao; Huang, Miaoqi	Correlative Analysis and Prediction of Physical Education Data Via Machine Learning: A Case Study on Grade Evaluation Method in University	2024	8	.pdf	application/pdf	5519	345	53	With the continuous in-depth study of data, various methods of processing and analyzing data have been developed[3]; by inviting student participation data and past performance data, classification and regression tasks are performed, and then artificial neural networks are used to obtain the highest overall Accuracy, providing comprehensive analysis and comparison, is the latest supervised machine learning technology used to solve the task of predicting student test scores, that is, discovering students in a high-risk dropout state, and predicting their future results, such as final exam results[4]. This article analyzes the details of physical fitness test results and the relationship with the comprehensive score.	cache/fcis-19452.pdf	txt/fcis-19452.txt