Polynomial regression is a form of nonlinear regression that describes nonlinear relationships in a dataset. There are several advantages to linear regression, mainly high accuracy. For your assignment, you will build a polynomial regression model in Python. The data is in a .CSV file that has the following information types. Position Level Salary Business Analyst 1 45000 Junior Consultant 2 50000 Senior Consultant 3 60000 Manager 4 80000 Country Manager 5 110000 Region Manager 6 150000 Partner 7 200000 Senior Partner 8 300000 C-level 9 500000 CEO 10 1000000 Using this data, our model should be able to predict the value of an employee candidate given their years of experience. The Python file must demonstrate the prediction of employee salary based on years of experience.
Polynomial regression is a form of nonlinear regression that describes nonlinear relationships in a dataset. There are several advantages to linear regression, mainly high accuracy. For your assignment, you will build a polynomial regression model in Python. The data is in a .CSV file that has the following information types. Position Level Salary Business Analyst 1 45000 Junior Consultant 2 50000 Senior Consultant 3 60000 Manager 4 80000 Country Manager 5 110000 Region Manager 6 150000 Partner 7 200000 Senior Partner 8 300000 C-level 9 500000 CEO 10 1000000 Using this data, our model should be able to predict the value of an employee candidate given their years of experience. The Python file must demonstrate the prediction of employee salary based on years of experience.
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Polynomial regression is a form of nonlinear regression that describes nonlinear relationships in a dataset.
There are several advantages to linear regression, mainly high accuracy.
For your assignment, you will build a polynomial regression model in Python.
The data is in a .CSV file that has the following information types.
Position | Level | Salary |
Business Analyst | 1 | 45000 |
Junior Consultant | 2 | 50000 |
Senior Consultant | 3 | 60000 |
Manager | 4 | 80000 |
Country Manager | 5 | 110000 |
Region Manager | 6 | 150000 |
Partner | 7 | 200000 |
Senior Partner | 8 | 300000 |
C-level | 9 | 500000 |
CEO | 10 |
1000000 |
Using this data, our model should be able to predict the value of an employee candidate given their years of experience.
The Python file must demonstrate the prediction of employee salary based on years of experience.
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