I’m addressing a project in which I really need to use distinctive estimators (regression models). could it be right use RFECV Using these styles? or is it plenty of to work with only one of these? Once I've selected the very best features, could I utilize them for every regression model?
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The sequence imposes an buy around the observations that have to be preserved when training products and building predictions.
I have a regression problem and I would like to convert a bunch of categorical variables into dummy knowledge, which will generate above two hundred new columns. Really should I do the attribute variety before this action or just after this action?