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What is the difference between Recursive Feature Elimination (RFE) function and SelectFromModel in Scikit-Learn? Both seems exactly similar.

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They effectively try to achieve the same result but the methodology used by each technique varies a little.

RFE removes least significant features over iterations. So basically it first removes a few features which are not important and then fits and removes again and fits. It repeats this iteration until it reaches a suitable number of features.

SelectFromModel is a little less robust as it just removes less important features based on a threshold given as a parameter. There is no iteration involved.

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