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Your code is correct and my result's similar to yours. My position is that the most effective features identified with RFE are preg, mass and pedi.
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I’m addressing a project exactly where I need to use various estimators (regression versions). is it right use RFECV with these versions? or can it be enough to utilize only one of these? At the time I have picked the ideal functions, could I rely on them for every regression model?
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Recipes takes advantage of the Pima Indians onset of diabetes dataset to display the element variety process (update: download from right here). That is a binary classification problem in which all the attributes are numeric.
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But then I need to offer these essential characteristics to your instruction design to create the classifier. I'm unable to provide only these critical characteristics as enter to develop the product.