Mental Health Prediction Using Machine Learning Algorithms

Different mental health issues, such as depression, stress, anxiety, and others, affect life in such a way that it is difficult for personal and professional life to not get severely ruined if not treated on time. The immediate recognition of the condition will ensure proper and best treatment for the patient so that they get the benefit of good health. This research applies Random Forest Classifier, Logistic Regression and Decision Tree Algorithms to evaluate their precision in mental health problem prediction and the stoppage of stress becomes the focus. The evaluation and comparison of their performance are, therefore, useful in bringing out the most reliable way to ensure early intervention for enhanced mental health and support for improved outcomes