Linear Regression — the power of the simplicity
Possibly, the most undervalued ML algorithm.
What does come into your mind when talking about the bleeding edge machine learning algorithm? Deep networks, transformers? Maybe gradient boosting tree algorithms? Whatever it is, I’m quite sure, that Linear Regression won’t be on the list.
And that shouldn’t be a surprise, as Linear Regression isn’t something we are used to calling the bleeding-edge algorithm in machine learning. It isn’t the most powerful ML technique out there. Linear Regression is one of the simplest ones. But still, it is very powerful and useful. Much more useful than many ML practitioners think. And this article will be exactly about that — the hidden power of Linear Regression.
To uncover this power, we’ll start with a simple example of an imagined situation.
The situation
Let’s imagine a small town. In this town, there are three small stores selling milk. The prices can differ a bit, but in general, they are mostly quite similar, as the town is small and owners of these stores are very well informed about how much milk costs in rival stores. If one store will have a much higher price, nobody will go to this store.
Let’s name these stores “Store A”, “Store B” and “Store C” for simplicity.
