Applying Machine Learning Technique to Understand the Suicidal Behavior in the Context of Bangladesh Age Group 12 to 35

Abstract

Suicide is a neglected preventable public health problem across the globe and Bangladesh is not an exception. Suicide can happen at any stage of life, it is the second most frequent and in some countries it is the leading cause of death among people aged 12–35 years. Suicide happens because of multi factorial involvement such as genetic, psychological, social, and cultural risk factors. The purpose of this recent study was to calculate the percentage of committing suicide based on the behavior of a person. A certain age group of people's information is being used to get the result. By understanding several Machine Learning algorithms are being used to develop a model that gives the result. Specific and standard questionnaires were asked to get the data from approximately one thousand people via offline and online. The data was then analyzed and preprocessed. Then seven Machine Learning Algorithms were applied. The result that showing a person's individual percentage of committing suicide and it has a correlation with Depression, Stress and Sexual Harassment.