Optimizing Virtual Reality Solutions for Predicting English Online Network Performance Using the XGBoost Algorithm

被引：0
作者：
Liu J. [1 ]
机构：
[1] Jiangxi Institute of Applied Science and Technology, Jiangxi, Nanchang
来源：
Computer-Aided Design and Applications | 2024年 / 21卷 / S17期
关键词：
conversion; data source; grade prediction; Virtual Reality Solutions; XGBoost algorithm;
D O I：
10.14733/cadaps.2024.S17.49-62
中图分类号：
学科分类号：
摘要：
In view of the current informatization needs of English learning and the advantages of deep learning algorithms, an English grade prediction based on the XGBoost algorithm is proposed. In order to verify the validity of the model in English score prediction, the principle of the XGBoost algorithm is firstly analyzed, and then the English test scores of a college from 2019 to 2021 are used as the basic data source, and the probability in the XGBoost algorithm model is used to compare the results under different attributes. Students' English grades are predicted, and the results show that the grades predicted by the XGBoost algorithm are basically consistent with the actual grades. © 2024 U-turn Press LLC.
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页码：49 / 62
页数：13
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