As the COVID-19 keeps unleashing its havoc, the world continues to get pushed into the crisis of the great economic recession, more and more companies start to cut down their underperforming employees. Companies firing hundreds and thousands of Employees is a typical headline today. Cutting down employees or reducing an employee salary is a tough decision to take. It needs to be taken with utmost care as imprecision in the identification of employees whose performance is attriting may lead to sabotaging of both employees' career and the company's reputation in the market.
To predict Employee Attrition by the given data about his/her past history.
This dataset is taken from one of the competition on Kaggle. The classification goal is to predict the Employee Attrition as Cutting down employees or reducing an employee salary is a tough decision to take. It needs to be taken with utmost care as imprecision in the identification of employees whose performance is attriting may lead to sabotaging of both employees' career and the company's reputation in the market.
Dataset Description:
*Id - an anonymous id given to an Employee
*Age - Age of an Employee
*Attrition - Did the Employee leave the company, 0-No, 1-Yes
*BusinessTravel - Travlling frequency of an Employee
*Department - Work Department
*DistanceFromHome - Distance of office from home
*EducationField - Field of Education
*EmployeeNumber - Number of Employees in the division of a given Employee
*EnvironmentSatisfaction - Work Environment Satisfaction
*Gender - Gender of Employee
*MartialStatus - Martial Status of an employee
*MonthlyIncome - Monthly Income of Employee in USD
*NumCompaniesWorked - Number of Companies in which Employee has worked before joining this Company
*OverTime - Does The person work overtime
*PercentSalaryHike - Average annual salary hike in percentages
*StockOptionLevel - Company stocks given to an Employee
*TotalWorkingYears - Total working experience of an employee
*TrainingTimesLastYear - No. of trainings an employee went through last year
*YearsAtCompany - Number of years worked at this company
*YearsInCurrentRole - Number of years in current role
*YearsSinceLastPromotion - Number of years since last promotion
*YearsWithCurrManager - Number of years with the current manager
ROC_AUC_SCORE
Ongoing