Salary Prediction By Polynomial-Regression

Project Objective

Lets assume the above table is what the HR team of a company uses to determine what salary to offer to a new employee. For our project, let's take an example that an employee has applied for the role of a Regional Manager and has already worked as a Regional Manager for 2 years. So based on the table above - he falls between level 6 and level 7 - Lets say he falls under level 6.5 We want to build a model to predict what salary we should offer this new employee.

Methodology:

1.EDA:

• Performed EDA to get more informative features like null values,outliers,correlation and other features.

2.Model Bulding:

1. Linear Regression Model
2. Plynomial Regression Model

3.Model Validation:

1. R-square value
2. Mean Squared error
3. Mean Absolute error

Insights:

• From both the prediction models the Polyomial regression model got the higher accuracy of 99.74 than Linear Regression model.
• So, according to the analysis, the polynomial regression is most efficient for the prediction of salary of the employees.