Depression Analysis On Final Year Undergraduate Students Through Machine Learning Techniques

Depression is becoming more apparent where it determines the overall wellbeing of societies and countries. When a person goes through a time span in final year, can fall into depression as their roles and responsibilities change. Under-graduation time is the important time for this type of transformation. Sometimes few factors cause serious mental effect on the students. Therefore, this study wants to investigate the depression levels of the university students. Gender, residential status, cumulative grade point average (CGPA) and year of studying etc. are considered as influencing factors of depression.
So, in this research work, we have proposed a method with a machine learning technique that classify depression. Also, we will detect why final year undergraduate students always stay in depression. Using simple random sampling, 602 data of final years’ undergraduate student different public and private university of Bangladesh.

Full Paper Link:

https://drive.google.com/file/d/1aHdp3lKja-ARd3AEk-JEuL0J_GIpjaZr/view?usp=sharing