Tree MAE fix to ensure sample_weights are used during impurity calculation #1
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JohnStott
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Jul 19, 2018
* Add averaging option to AMI and NMI Leave current behavior unchanged * Flake8 fixes * Incorporate tests of means for AMI and NMI * Add note about `average_method` in NMI * Update docs from AMI, NMI changes (#1) * Correct the NMI and AMI descriptions in docs * Update docstrings due to averaging changes - V-measure - Homogeneity - Completeness - NMI - AMI * Update documentation and remove nose tests (scikit-learn#2) * Update v0.20.rst * Update test_supervised.py * Update clustering.rst * Fix multiple spaces after operator * Rename all arguments * No more arbitrary values! * Improve handling of floating-point imprecision * Clearly state when the change occurs * Update AMI/NMI docs * Update v0.20.rst * Catch FutureWarnings in AMI and NMI
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Tree MAE is not considering sample_weights when calculating impurity!
In the proposed fix, you will see I have multiplied by the sample weight after applying the absolute to the difference (not before). This is in line with the consensus / discussion found here, where negative sample weights are considered: scikit-learn#3774 (and also because during initialisation, self.weighted_n_node_samples is a summation of the sample weights with no "absolute" applied (this is used in the impurity division calc)).
Reference Issues/PRs
Fixes: scikit-learn#11460 (Tree MAE is not considering sample_weights when calculating impurity!)