A Machine Learning Framework for Ranking Cities Considering Crimes Against Women: A Case Study in Northeast Brazil - Turet, Jean; Nepomuceno, Thyago (Anais do Workshop sobre as Implicações da Computação na Sociedade (WICS); 2025: Anais do VI Workshop sobre as Implicações da Computação na SociedadeDO - 10.5753/wics.2025.7930, 2025)
Violence against women is a profound infringement of human rights and stands as one of the most severe public health issues globally. It is comprehensively defined as any act of physical, sexual, psychological, or property-based violence perpetrated against a woman, constituting behaviour that transgresses women's dignity, rights, and freedom. In this context, this study introduces a machine learning model aimed at classifying cities based on the potential prevalence of violence against women. The model is trained utilizing a comprehensive city database, generating classifications of cities into three levels: low, medium, and high violence. The chosen algorithm, ExtraTrees, demonstrated a noteworthy accuracy rate of 90%.