使用机器学习算法的离婚预测在哈伊尔地区,KSA.
Abdelkader Moumen1, Ayesha Shafqat2, Tariq Alraqad3
1Department of Mathematics, College of Science, University of Ha'il, Ha'il, 55473, Saudi Arabia. mo.abdelkader@uoh.edu.sa.
Scientific reports
|January 4, 2024
概括
这项研究使用机器学习算法测试离婚预测量表 (DPS) 预测离婚. 离婚预测量表有效地使用随机森林算法预测了91.66%的准确度的离婚.
科学领域:
- 社会科学 社会科学 社会科学
- 心理学 心理学 心理学
- 计算机科学 计算机科学
背景情况:
- 离婚是一个重要的社会问题.
- 人工智能 (AI) 和预测分析为社会问题提供了新的解决方案.
- 哥特曼夫妇治疗框架提供了关系成功的预测指标.
研究的目的:
- 评估离婚预测量表 (DPS) 在预测离婚方面的有效性.
- 为了确定导致海尔地区离婚的关键因素,KSA.
- 应用机器学习算法用于离婚预测.
主要方法:
- 使用了54项离婚预测量表 (DPS) 和个人信息表格.
- 收集了148名参与者的数据 (116名已婚,32名离婚).
- 应用机器学习算法:人工神经网络 (ANN),天真贝叶斯 (NB) 和随机森林 (RF).
- 采用基于相关性的特征选择来识别顶级预测因素.
主要成果:
- 随机森林 (RF) 算法实现了最高的准确率91.66%.
- 这项研究证实了DPS对离婚的预测能力.
- 确定了有助于预测离婚的关键特征.
结论:
- 离婚预测量表 (DPS) 是预测离婚的有效工具.
- 结果支持戈特曼预测器在哈伊尔地区的适用性,KSA.
- 家庭心理医生可以协助家庭咨询师和治疗师进行干预计划.
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