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Application of machine learning in the prediction of drawing test ondependent personality dysfunction in adolescents
Authors
林轩
王亚
+6 more
王鹏罛
罗捷
裴欢昌
邢怡伦
陈涛
项锦晶
Publication date
1 January 2019
Publisher
Abstract
目的:运用机器学习探索绘画测验对青少年依赖型人格偏离的预测力。方法:研究样本是318例青少年,采用人格障碍诊断问卷的依赖型人格障碍分量表来评定青少年的依赖型人格偏离,借助统合型“房树人”绘画测验分析其绘画特征。共筛选出依赖型人格偏离阳性组79例,阴性组239例。运用机器学习探讨11项绘画特征对依赖型人格偏离的预测性能。结果:在对青少年依赖型人格偏离的预测中,所选取的11项绘画特征中,树干、伤痕(0.20)、人靠近树(0.18)和中心画(0.13)3个特征的平均重要性最高。机器学习模型预测的准确率为0.87,精度为0.85,召回率为0.86,F1分数为0.85。结论:绘画测验结合机器学习能较好地预测青少年依赖型人格偏离。</p
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Last time updated on 05/12/2019