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I want to add some thoughts on the problem at hand, so that the discussion may roll on. However, I propose something else to think about, so others may comment on this. When reading this post and the post in the highlighted link, we try to overcome the bias in the RF (possibly in the tails) and to correct biased output of the RF, by applying another method, ...


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One should not perform exploration/variable selection and inference on the same sample of observations. The $p$ values are no longer valid (i.e., too low) if you use the exact same data to select the predictor variables, first. For performing hypothesis tests (inference), you need to have specified a-priori hypotheses. From these data, you have extracted the ...


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It may be an old question, but for you and others, who came across elastic net in the caret package, I would rely on lambda thus your weight decay mainly: As you can also see here in this picture, which is similar to your plot, you are looking for a general turning point, or break even: What you have done is mainly one technique in ML, 'narrowing down the ...


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