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This was a generic question. I did not include code because I did not want to solve a specific problem. I never stated I'm a data scientist and... IMHO it is not necessary to be so "rude" :). Thank you anyway for the explanation.
Thanks. I'm writing a report and I wanted to show the linear/non-linear correlations in order to justify the features (even before the results). Does it make any sense? From your answer I could make a matrix of correlations but maybe it's nosense
I always thought to compare the value to predict with the features, you are talking about correlation between features. Is your answer applicable also to my case? in theory I should add only new features that are correlated to the value to predict, right?