EMPLOYEE SALARY PREDICTION USING MULTI MODEL MACHINE LEARNING TECHNIQUES: A COMPARATIVE ANALYSIS

摘要

Generally, job advertisements don't mention the salary for a particular designation. So, this project is used to predict the salary of an employee based on certain parameters like designation, skillsets & his/her experience in the industry. The project is done by comparing each parameter of every individual so that the salary of a person can be predicted. The project is implemented using Python code & Machine learning models. In the front end, a web page will be created to show the predicted salary, this is done by HTML, CSS. In the backend, the model is trained with multiple ML models and compared based on various parameters like accuracy and algorithm performance. Algorithms are Logistic Regression with the accuracy of 31%, Decision Tree with 100% & Random Forest with 100%. Based on the algorithm performance, a random forest is more efficient than a decision tree. So it is used for deployment. Later, for future developments, we can predict the salary of all the employees from a particular company at once.