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Feature Selection in a Machine Learning Process?
You always have to train a model twice, because the first time you train a is for feature selection. You are training a model with a thousand rit fa of the original variables. And if they become useless on this corse variation t which is essentially a outer semble test set, you will kep meu with wank and blow. That's at thebante of o his schime got an interesting question here from bk capital. E weren't too many variables or features. I guess just confused the modo i sorye model. The edges are slim already, right? So as i said, they are well established. Technique te the notion of features importance ranking