Overview

• A linear regression is the approximation of a linear model used to describe the relationship between two or more variables.
• The two types of variable in a linear regression are:

Mathematical Background

• The equation of a simple linear model is:

Process of Operation

• Once the model is trained on some training data, we input variables into the model, and the weighted (with bias added) output is the prediction of our model.

Training

• Once a linear model has been trained on a set of data, it can also be known as a 'line of best fit' for that data.
• The line of best fit is found by
• NOTE: in simple terms Linear Regression and Line of Best Fit are the same thing, but in practice, Linear regression can also be trained using more complex terms than just least squares regression.

Citations

(n.d.). What’s the difference between the regression line and the line of best fit? - Quora. Retrieved from https://www.quora.com/Whats-the-difference-between-the-regression-line-and-the-line-of-best-fit