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Showing content from https://github.com/scikit-learn/scikit-learn/issues/13286 below:

IterativeImputer shouldn't just use l2 loss by default · Issue #13286 · scikit-learn/scikit-learn · GitHub

@GaelVaroquaux points out that iterative imputation with a regularised least-squares model is more-or-less the same as using NMF for imputation. We should instead use RandomForestRegressor as the default regressor in IterativeImputer, at least if sample_posterior=False (or we can implement predict(return_std=True) on RandomForestRegressor!).


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