This is a machine learning project based on the 'HR-comma-sep.csv' dataset.
This model tries to predict whether or not an employee will resign from the company given a certain parameters.
This is project uses Logistic Regression to accomplish this task.
The independent variables are: a)Satisfaction level: satisfaction level at job of an employee b)last_evaluation: Rating between 0 to 1, received by an employee at his last evaluation c)number_project: Number of projects, an employee is involved in d)average_monthly_hours: Average number of hours in a month, spent by an employee at office e)time_spend_company: Number of years spent in the company d)Work_accident: 0 - no accident during employee stay, 1 - accident during employee stay e)promotion_last_5years: Number of promotions in his stay f)Department: Department an employee belongs to g)salary: Salary in USD
The dependent variable is: left: 0 indicates employee stays in the company, 1 indicates - employee left the company
Both the dataset and the saved version of the model are provided in this repository. The model has an r2 score of 0.802(approximately).