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Scikit learn has a make_regression data generator. Can someone explain it to me like I'm 5 what is meant in the help docs by "The input set can either be well conditioned (by default) or have a low rank-fat tail singular profile"?

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Well-conditioned: the data is well formatted for the regression task.

Low rank: the input has low dimensional data.

Fat tail: the dataset has a lot of extreme values, which could be challenging as the distribution is unbalanced.

Singular profile: specific distribution.

On a whole, make_regression is able to make many kinds of random regressions problems, from simple distributions (well-conditioned) to very complex ones (singular).

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