Machine learning: Prediction suicidal behaviour based on drug abuse and mental health
There is some well-known correlation between certain mental disorders and suicidal ideation or suicidal behaviour. I was interested in whether a machine learning model could be trained to identify suicidal behaviour based on mental health, biological health, and drug abuse questions. The dataset I was working with came from the public Criminal Justice Drug Abuse Treatment Studies (CJ-DATS): The Criminal Justice Co-Occurring Disorder Screening Instrument (CJ-CODSI) and had new 353 new admissions to a prison-based substance abuse treatment program (137 Whites, 96 African Americans, and 120 Latinos). The questionnaire, created by psychologists , overall was very detailed with 789 attributes, either direct data input or compound fields, based on other fields. The variable I wanted to forecast was called SATTLF (Suicide Attempts Lifetime) and to make sure that no suicide or suicide-related questions were left in the source data, I removed 164 fields (including SATTLF), which direct...