The impact of analysis Suicide using machine learning algorithms in Ardabil: A performance analysis : using machine learning algorithms in analysis Suicide

Suicide in Iran is believed to be a growing concern over recent years. According to World Health Organization, in 2019, the suicide rate in Iran was 5.20 in every 100,000 people. In that year, the rate of suicide based on gender was 2.80 for women and 7.70 for men. This article examines an attempt to determine the role of clustering algorithms (Filter, Wrapper, embedding, and machine learning algorithms) in identifying effective factors in suicide attempts. We focus on developing feature selection methods that distinguish between high-variance features in the likelihood of individuals committing suicide. Suicide dataset is collected from an Ardabil University of medical sciences containing 600 patient reports with 28 attributes.