IJFANS International Journal of Food and Nutritional Sciences

ISSN PRINT 2319 1775 Online 2320-7876

An improved method for Detection of Employee Stress Using Machine Learning.

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MUSUNURU RATNAKAR, SWATHI TERLI, PILLEM RANI, G VENKATA PRADEEP KUMAR

Abstract

Disorders of stress are very casual thing among the employees who are working in corporate sectors. As with changing work of people and their living lifestyle, we can see the increment of stress in the working employees. Even many corporate sectors are providing variety of schemes related to mental health and trying to reduce the disorders of stress in the working environment, the disorder is very far from stopping. In our paper, we are going to make use of two techniques of machines to determine the amount of stress the employee is having who is working in corporate sectors and try to narrow down the issues that identify the stress levels. We are going to apply two techniques of machine learning (i.e. SVM and Random Forest) when the data preprocessing and the cleaning of data is once finished. The correctness of our trained model was clearly read and analyzed. By using these two techniques of machine learning, the main features that result in disorders of stress are found to be as sex, background of family and ease of benefits of health in the working place of employee. With these results, corporate industries can now narrow down the stress and can establish a very friendly working place for the corporate sectors employees.

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