Uncovering the Most Important Factors for Predicting Sexual Desire Using Explainable Machine Learning

Vowels Laura M.; Vowels Matthew J.; Mark Kristen P.

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Uncovering the Most Important Factors for Predicting Sexual Desire Using Explainable Machine Learning

机译：Uncovering the Most Important Factors for Predicting Sexual Desire Using Explainable Machine Learning

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Background: Low sexual desire is the most common sexual problem reported with 34% of women and 15% of men reporting lack of desire for at least 3 months in a 12-month period. Sexual desire has previously been associated with both relationship and individual well-being highlighting the importance of understanding factors that contribute to sexual desire as improving sexual desire difficulties can help improve an individual's overall quality of life.

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来源
《The journal of sexual medicine》 |2021年第7期|1198-1216|共19页
作者
Vowels Laura M.; Vowels Matthew J.; Mark Kristen P.;
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作者单位

Univ Southampton, Dept Psychol, Southampton, Hants, England;

Univ Surrey, Ctr Comp Vis Speech & Signal Proc CVSSP, Guildford, Surrey, England;

Univ Minnesota, Med Sch, Dept Family Med & Community Hlth, Minneapolis, MN USA;

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原文格式 PDF
正文语种英语
中图分类性卫生;
关键词
Close Relationships; Sexual Desire; Machine Learning; Random Forests; Shapley Values;

Uncovering the Most Important Factors for Predicting Sexual Desire Using Explainable Machine Learning

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