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Your code is right and my result's similar to yours. My place would be that the most effective characteristics discovered with RFE are preg, mass and pedi.
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I’m handling a project wherever I should use distinctive estimators (regression products). can it be proper use RFECV Using these designs? or is it plenty of to employ only one of these? The moment I've picked the best options, could I utilize them for each regression design?
Recipes uses the Pima Indians onset of diabetic issues dataset to show the feature assortment technique (update: obtain from listed here). This is the binary classification dilemma where all of the attributes are numeric.
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I’m focusing on a private project of prediction in 1vs1 sports activities. My neural network (MLP) have an accuracy of sixty five% (not great nonetheless it’s a superb commence). I have 28 options And that i imagine that some have an impact on my predictions. So I used two algorithms mentionned as part of your post :