Mental Health Quantifier
Daksh Gupta1, Aashay Markale2, Rishabh Kulkarni3

1Daksh Gupta*, Department of Information Technology, College of Engineering, Pune (Maharashtra), India.
2Aashay Markale, Department of Information Technology, College of Engineering, Pune, (Maharashtra), India.
3Rishabh Kulkarni, Department of Information Technology, College of Engineering, Pune, (Maharashtra), India.

Manuscript received on May 21, 2021. | Revised Manuscript received on May 26, 2021. | Manuscript published on June 30, 2021. | PP: 187-190 | Volume-10 Issue-5, June 2021. | Retrieval Number: 100.1/ijeat.E26940610521 | DOI: 10.35940/ijeat.E2694.0610521
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Abstract: The definition of mental disorders describes them as “health conditions involving changes in emotion, thinking or behavior or a combination of these”. Contemporary societies of 2020 still fall short in recognizing some of the most common afflictions as actual problems in people. Some of those are depression, anxiety and stress disorders. This paper proposes a Machine Learning based approach wherein the analysis of the multiple-choice inputs along with a neatly curated questionnaire based on feature extraction will be done and then supervised classification algorithms will be used to generate a mental health score as well as a detailed report based on responses the user gives. 
Keywords: Classification, Feature Extraction, Machine Learning, Mental Health, Psychology