HUMAN BEHAVIOUR RECOMMENDATION SYSTEM USING MACHINE LEARNING
DOI:
https://doi.org/10.29121/shodhkosh.v5.i2.2024.1613Keywords:
Data Science, Artificial Intelligence, Machine Learning, Personality TraitsAbstract [English]
During early adolescence, most mental disorders emerge, which contribute significantly to the global mental health burden, including India. Early identification of mental health problems is a major challenge in India. This study aimed to evaluate the effectiveness of mental health interventions among adolescents in India, and investigate personality patterns and psycho-social functioning among them using Machine Learning techniques. After conducting a literature review on Pub Med, Research gate and government websites, it was concluded that longitudinal study designs can be more efficient, less costly, and more robust to model selection, and they can have increased statistical power. The k means clustering technique was used to analyze personality patterns based on the Big 5 personality test. Psychological distress can be linked to personality patterns or traits, which refer to an individual's enduring patterns of thoughts, feelings, and behaviors that shape their characteristic ways of responding to and coping with the world around them.
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Copyright (c) 2024 P. A. Kharade, Rajendra B. Mohite, Sandip S Kanase
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