Discovering linear regression
Linear regression is one of the simplest techniques that we can apply when we have a continuous numerical value to predict. It is a well-known algorithm that was initially introduced in statistics to analyze the correlation between different variables.
Important note
In statistics, the term regression means that two variables are correlated. This term describes a cause and effect relationship. The cause is called the independent variable, while the effect is called the dependent variable. The dependent variable can be calculated as a function of the independent variable.
The following diagram shows the graphical representation of a simple linear relationship between two variables:
Figure 4.2 – Representation of simple linear regression
A linear regression model tries to predict the label by finding the best linear relationship between the label and its features. If the machine learning model uses only one input...
