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iyeva t1_j4pwopf wrote

Does this not already exist in permutation_importance() in sklearn? That is also calculating the feature importance based on permutated data. I think the technique was first described in Olden et Al. 2004, so I would be surprised if there aren't even more implementations by now.

Or am I missing something different here?

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cblume OP t1_j4qwpte wrote

Similar idea in that features are perturbed but both algorithms are quite different. E.g. sklearn uses scores but featureimpact doesn't; sklearn uses random perturbations but featureimpact uses quantiles.

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