A Comparative Analysis of Four Classification Algorithm for Mental Health Analysis basis on technical People

Abstract

Mental disorder is a disorder of the mind that softens the effects of extreme discomfort in thinking and over-behaving, which fails to adapt to the normal needs and routines of life. In contrast, technology is rapidly evolving society and numerous practices now require the ability to use technology. These situations can induce problems for many people, including users with severe mental illness technology. In this study, we have tried to demonstrate a comparative analysis of four classification algorithm for mental disorder of technical people. Many researchers analyses the mental health. None of them are analysis the mental health to find out the identification reason of mental disorder among the tech people in the tech workplaces. This paper objective is Finding the predicted causes of mental illness or mental disorder in tech work places and visualizing the correlation among the causes. This paper proposed a model for identifying the reason of mental illness among the technical people. There we used Correlation to select features and showing the comparison of the result we used Decision Tree, Naïve Bayes, ANN and KNN. Elbow method is used to determine the optimal k. After the dataset analysis, the frequency of occurrence of mental disorder among these technicians is 22-24 years of age and the location of the work is system admin, back end developer, stack developer, team leader. We need to take the necessary steps to raise awareness of mental illness among tech people. If we fail to take the necessary steps, this problem will become more and more complex, and this problem will be very difficult to solve at once. Therefore, this research would yield the potential for healthier lives for countless individuals and the general advancement of the nation's wellbeing.