Now that other blog posts in this article series have helped us understand different types of variables, let’s look at some ways they can relate to each other, and how that can help us understand sets of data.
The first and more straightforward group of algorithms use regression.
This is a way of looking at the relationship between variables and can predict the dependent variable based on known values of the independent variables.
Regression algorithms predict a numeric value in any range.
For example, if we know that a customer is a woman with a high salary (independent variables), then we can predict how much she might spend on certain items (dependent variable).
Let’s break it down a little, and have a look at how different regression algorithms work:
If you want to read all the related articles on the topic of AI algorithms, here is the list of all blog posts in this article series:
