I have a dataset which contains equally categorical and numerical options. Must I do aspect variety in advance of a single-scorching encoding of categorical features or after that ?
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Commonly, I like to recommend generating many alternative “sights†over the inputs, in shape a model to every and Assess the performance in the ensuing models. Even Mix them.
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If the user has a called number on their own board, the variety may very well be removed from the listing along with the board redrawn. You might also build An additional plan to the caller, to create the figures.
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…is you may possibly get the exact same number a lot more than as soon as. So how can we make sure that we get 10 different figures?
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Your code is correct and my result is the same as yours. My level would be that the finest features identified with RFE are preg, mass and pedi.
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