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Development of a Classification Model for Mental Health

Authors

Wei Yihai

Rubric:Medicine and healthcare
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Mental health includes our emotional, psychological, and social well-being. It affects how we think, feel, and act. This paper will use the logistic regression to classify whether the person sought to have some mental health treatment. The final model results show that our model has achieved an AUC value of over 0.86, indicating a powerful strength to predict the mental health reorganization of individuals. Also, the report presented that the top factors that influence the mental health condition are age, gender and family history.

Keywords

mental health
AUC
logistic regression
correlation analysis

Authors

Wei Yihai

References:

[1] Pedrelli, P., Nyer, M., Yeung, A., Zulauf, C., & Wilens, T. (2015). College students: mental health problems and treatment considerations. Academic Psychiatry39(5), 503-511.

[2] Hilbe, J. M. (2009). Logistic regression models. Chapman and hall/CRC.

[3] Wang, H., Xu, Q., & Zhou, L. (2015). Large unbalanced credit scoring using lasso-logistic regression ensemble. PloS one10(2), e0117844.

[4] Narkhede, S. (2018). Understanding auc-roc curve. Towards Data Science26, 220-227.

[5] Malhi, A., & Gao, R. X. (2004). PCA-based feature selection scheme for machine defect classification. IEEE transactions on instrumentation and measurement53(6), 1517-1525.

[6] Essex, M. J., Kraemer, H. C., Armstrong, J. M., Boyce, W. T., Goldsmith, H. H., Klein, M. H., ... & Kupfer, D. J. (2006). Exploring risk factors for the emergence of children's mental health problems. Archives of general psychiatry63(11), 1246-1256.

[7] Kirasich, K., Smith, T., & Sadler, B. (2018). Random forest vs logistic regression: binary classification for heterogeneous datasets. SMU Data Science Review1(3), 9.

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