Predicting-Employee-Attrition
Objective
Using machine learning to predict employee attrition in Python.
Data Description
The dataset consists of 25491 obseravtions and 10 variables. Each row in dataset represents an employee; each column contains employee attributes:
- satisfaction_level (0–1)
- last_evaluation (Time since last evaluation in years)
- number_projects (Number of projects completed while at work)
- average_monthly_hours (Average monthly hours at workplace)
- time_spend_company (Time spent at the company in years)
- Work_accident (Whether the employee had a workplace accident)
- left (Whether the employee left the workplace or not (1 or 0))
- promotion_last_5years (Whether the employee was promoted in the last five years)
- sales (Department in which they work for)
- salary (Relative level of salary)
Approach
We perform turnover analysis project by using Python’s Scikit-Learn library. I have used Decision Tree, Gradient Boosting Regressor for calculating Accuracy.
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