基于机器学习算法对大学生手机成模型的影响因素细分和智能预测模型的构建
Yun Hong1, Xing Rong2, Wei Liu2
1Jiyang College, Zhejiang A&F University, Zhuji, Zhejiang, 311800, China.
Heliyon
|April 19, 2024
概括
大学生大学的学生.
科学领域:
- 心理学 心理学 心理学
- 计算机科学 计算机科学
- 公共卫生 公共卫生
背景情况:
- 手机成是大学生日益关注的问题.
- 它显著影响学生的发展和福祉.
- 评估和预测这种成是非常重要的.
研究的目的:
- 确定导致大学生手机成的关键因素.
- 开发一种基于机器学习的手机成预测模型.
- 为评估成水平提供可靠的工具.
主要方法:
- 来自中国一所公立大学的3000名大学生参与了这项研究.
- 调查问卷数据被收集和分析.
- 机器学习算法被用来识别因素并构建一个预测模型.
主要成果:
- 完美主义被认为是影响手机成的主要因素.
- 一个机器学习预测模型实现了76.68%的准确性.
- 该模型证明了对未来评估的可靠性.
结论:
- 完美主义是大学生手机成的重要预测因素.
- 机器学习为预测和评估手机成提供了一种可行的方法.
- 开发的模型可以帮助早期检测和干预策略.
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