山东大学学报 (工学版) ›› 2024, Vol. 54 ›› Issue (4): 76-85.doi: 10.6040/j.issn.1672-3961.0.2024.057
乔慧妍1,段学龙1,解驰皓2,赵冬慧1,马玉玲1*
QIAO Huiyan1, DUAN Xuelong1, XIE Chihao2, ZHAO Donghui1, MA Yuling1*
摘要： 采用异常点检测算法研究心理健康辅助诊断任务,提出并设计一种基于异常点检测的心理健康辅助诊断方法,有效识别心理沙盘数据中的异常样本。在构建心理健康辅助诊断模型过程中,分析数据特性,提取与用户心理健康状况高度相关的特征,构建虚拟心理沙盘数据集;使用4种传统异常点检测算法,识别沙盘数据集中异常样本,设计融合策略,集成不同算法检测结果,提高异常样本检测精准性和效率,辅助人类专家进行精确诊断;对模型预测性能和结果进行详细分析,结合基线模型进行对比评价。试验结果表明,基于异常点检测的心理健康辅助诊断方法在沙具使用相似度、距离度量、聚类性能等3项指标上获得较好性能。
中图分类号:
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