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What is ML Algorithms for Predicting Student Mental Health about?

This study evaluates the effectiveness of various machine learning algorithms in predicting depression and anxiety among university students in Bangladesh during the COVID-19 pandemic. A survey of 2121 students revealed that the Random Forest algorithm was most accurate for predicting depression (89% accuracy), while the Support Vector Machine algorithm was best for anxiety prediction (91.49% accuracy). The research highlights the importance of using machine learning techniques to assess mental health statu

Author

lasnisinta11

Language

EN