Facial Beauty Standards Predictions Based on Machine Learning: A Comparative Analysis

Sadiq, Bareen Haval
Abdulazeez , Adnan M.

The Indonesian Journal of Computer Science
Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science (IJCS)

This study uses a variety of machine learning and classification methods to anticipate the Facial Beauty Standards. The Accuracy of five different models—Random Forest, Logistic Regression, Support Vector Machine (SVM), KNN, and decision tree—were used to analyses each one. There were noticeable differences in the models' performances. In particular, the Logistic Regression and SVM methods demonstrate almost perfect accuracy, followed closely by random forest and KNN. This study gives insight into how well different models perform in comparison and emphasizes the benefits and drawbacks of each in terms of predicting face beauty standards.