This was my work for HackerEarth: Employee Burnout Hackathon
I only discovered it as it was about to end, so couldnt work on it a much
A few plots for eda, followed by model building and creation of submission file
To read more about the problem: https://www.hackerearth.com/problem/machine-learning/predict-the-employee-burn-out-rate-7-6340b4e3/
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.