Problem Statement

World Mental Health Day is celebrated on October 10 each year. The objective of this day is to raise an awareness about mental health issues around the world and mobilise efforts in support of mental health. According to an anonymous survey, about 450 million people live with mental disorders that can be one of the primary causes of poor health and disability worldwide. You are a Machine Learning engineer in a company. You are given a task to understand and observe the mental health of all the employees in your company. Therefore, you are required to predict the burn out rate of employees based on the provided features thus helping the company to take appropriate measures for their employees.

Data

• train.csv (22750 x 9)
• test.csv (12250 x 8)
• sample_submission.csv (5 x 2)

Variable Description

Column Name	Description
Employee ID	Unique Id of the employee
Date of Joining	Date on which the employee joined the company
Gender	Gender of the employee
Company Type	Type of company eg: Service based, product based etc.
WFH Setup Available	Whether proper work from home setup is available or not
Designation	Seniority level of the employee in codes
Resource Allocation	Hours allocated per day
Mental Fatigue Score	Stress rating provided by employees
Burn Rate	Rate of saturation or burn out rate [Target]

Submission format

You are required to write your predictions in a .csv file that contain the following columns:

• Employee ID
• Burn Rate

Evaluation criteria

The evaluation metric that is used for this problem is the r2_score. The formula is as follows:

Acknowledgements

https://www.hackerearth.com/challenges/competitive/hackerearth-machine-learning-challenge-predict-burnout-rate/