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So, I suggest you deal with the text “You can see that RFE chose the the highest three attributes as preg, pedi and age.â€. In case you incorporate the code below at the end of your code you will notice what I imply.
I'm greatly impressied by this tutorial. I am merely a rookie. I have an exceptionally fundamental dilemma. After I obtained the lowered Variation of my facts because of using PCA, how am i able to feed to my classifier? I indicate to say tips on how to feed the output of PCA to develop the classifier?
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How can I am aware which function is more significant with the product if you can find categorical options? Is there a technique/way to work out it prior to a single-incredibly hot encoding(get_dummies) or how to estimate after a single-sizzling encoding if the model just isn't tree-based?
I’m dealing with a project exactly where I need to use distinct estimators (regression types). is it accurate use RFECV with these products? or is it more than enough to work with only one of them? At the time I've chosen the top features, could I use them for each regression model?