Data Mining-based Classification Methods for Mental Health Prediction

The advancement of mental health education and prognosis is crucial since the mounting pressures of contemporary society have contributed to an increase in psychological issues. In order to assess mental health intelligence, this research work suggests a method that makes use of data mining and classification algorithms. An improved method is created to overcome the shortcomings of existing methods by integrating decision trees with Artificial Neural Network (ANN) algorithms. Using data mining-derived compound learning algorithms, the system analyses and classifies mental health IQ test data. To assess the system's effectiveness and superiority, novel simulation tests are carried out. In order to increase accuracy and efficacy, the research also presents new methods for assessing mental health intelligence. While ensuring stability, the suggested system seeks to address the drawbacks of the current approaches.