Stress Level Prediction of College Students Using ML

Abstract

College students' mental health is often neglected, which may have serious consequences for their success in academic records. Mental health issues among college students may have far-reaching consequences for both the campus and the students themselves. General counselling, student management systems, and human advisers are just some of the ineffective approaches that institutions are using to track and avoid student stress. Naive Bayes, K-Nearest Neighbor, and Decision Tree are just a few examples of the Machine Learning Algorithms used by the proposed system to determine whether or not a student is experiencing stress and, if student is in stress, the system provide solution for relieving that stress. Key Words: Machine Learning, Naïve Bayes, K-Nearest Neighbor, Decision Tree, Stress, Stress Free, Prediction