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That may be a good deal of recent binary variables. Your resulting dataset are going to be sparse (numerous zeros). Feature collection prior might be a good suggestion, also consider right after.
But I have some contradictions. For exemple with RFE I identified 20 functions to pick out though the element An important in Characteristic Significance just isn't selected in RFE. How can we describe that ?
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So, I recommend you correct the textual content “You could see that RFE selected the the top 3 attributes as preg, pedi and age.”. If you add the code under at the end of your code you will see what I suggest.
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The scikit-learn library offers the SelectKBest course that may be used with a set of various statistical exams to pick a specific quantity of options.
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