Data Science

Forward Selection for Feature Selection in Machine Learning

In our previous post, we saw how to perform Backward Elimination as a feature selection algorithm to weed out insignificant features from our dataset. In this post, we'll checkout the next method for feature selection, which is Forward Selection. As you can already guess, this is going to be the opposite of backward elimination, well kind of. But before that, make sure you make yourself familiar with the concept of P-value. Similar to backward elimination, even here we have a few steps to follow. We'll go one by one as usual. But before going in, you need to know that this is going to be a bit more tedious of a job than backward elimination, because you have to create a bunch of simple linear regression models here. And depending on the number of features you have in your dataset, the ...

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