International Journal Of Engineering Technology And Management Sciences

AUTHOR(S)

Gourab Karak, Kishalay Ghosh, Nur Muktada Hasan Ansari, Mrs. Sulekha Das, Dr. Avijit Kumar Chaudhuri

DOI: https://doi.org/10.46647/ijetms.2023.v07i02.006

ABSTRACT
Suicide is nowadays a crucial public health issue. In various communities, people are much more affected by this severe tendency. Nowadays, suicide connects to mental illness. Along with depression, drug misuse is an equally important risk factor. Although anxiety, personality, and trauma-related issues, as well as genetic and mental disorders, also equally contributed to this health issue. This research work conducts to find the relation among suicidal tendencies, depression, anxiety, daily stresses, and mental health among all people, including employees, non-employee, students, old age, and all others. Step-by-step multiple linear regression, logistic regression analyses, confusion matrix, and cross-validation use for the data analysis. Suicidal illusions have a significant and positive relation with depression, anxiety, mental stress, and drug use disorder. In this research work regression technique showed that depression is the most crucial feature in the prediction of suicidal behavior, where anxiety, mental health, and daily stresses are the next, followed by respectively. Psychological problems and mental health issues with other factors such as gender problems, marital problems, and hallucinations play a role in suicidal thoughts [1]. Through this research, approximately 84 percent (%) of the data predict correctly.

Page No: 38 - 46

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How to Cite This Article:
Gourab Karak, Kishalay Ghosh, Nur Muktada Hasan Ansari, Mrs. Sulekha Das, Dr. Avijit Kumar Chaudhuri . Prediction of suicidal tendencies using machine learning . ijetms;7(2):38-46. DOI: 10.46647/ijetms.2023.v07i02.006