Data Science

What is multicollinearity?

Image from StaticsticsHowTo Multicollinearity is a term we often come across when we're working with multiple regression models. Even we have talked about it in our previous posts, but do we know what it actually means? Today, we'll try to understand that. In most real life problems, we usually have multiple features to work with. And not all of them are in the format that we, or the model, wants. For example, a lot of categorical features are usually in the text format. But as we already know, our models require the features to be numerical. For this, we will label encode the feature and if required, we'll even one hot encode them. But in some cases, we might have features whose values can be easily determined by the values of other features. In other words, we can see a very go...

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