Regression is a statistical method for calculating relationships among variables. This section will implement linear regression, which is the most popular and simplest regression technique and a very good way to understand your data. Note that regression techniques are not 100% accurate, even if you use higher-order (nonlinear) polynomials. The key with regression, as with most machine learning techniques, is to find a good enough technique and not the perfect technique and model.
Regression
Linear regression
The idea behind linear regression is simple: you are trying to model your data using a first-degree equation. A first-degree equation can be represented as y = a x + b.
There are many methods that allow you to find out...
