Using machine learning to judge sexual faithfulness based on human perception of face

Yihang Liu; Wanying Dou

doi:10.1117/12.2646412

23 August 2022 Using machine learning to judge sexual faithfulness based on human perception of face

Yihang Liu, Wanying Dou

Proceedings Volume 12330, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022); 1233003 (2022) https://doi.org/10.1117/12.2646412
Event: International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022), 2022, Huzhou, China

Abstract

People will analyze the faithfulness of others through facial features and expressions when they come into contact with strangers. In mating choice, the accurate estimation of sexual unfaithfulness will reduce the reproductive cost of an unfaithful mate. Therefore, this paper uses machine learning to judge sexual faithfulness based on human perception of the face in four dimensions: attractiveness, trustworthiness, faithfulness, and sexual dimorphism. First of all, this study uses three conventional machine learning algorithms to classify the data. Then we use soft voting to build an ensemble model. The study reveals that women have better performance than men at judging sexual faithfulness. Moreover, the AUC of our ensemble model is 0.861 based on female and 0.789 based on male.

Citation Download Citation

Yihang Liu and Wanying Dou "Using machine learning to judge sexual faithfulness based on human perception of face", Proc. SPIE 12330, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022), 1233003 (23 August 2022); https://doi.org/10.1117/12.2646412

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