Fix handle_missing parameters and standardize input data shape for MinHashEncoder - #210
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Can you fix the conflicts and update the changelog please. |
alexis-cvetkov
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LilianBoulard
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LGTM, thanks for the contributions !
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Merging ! |
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I have made small modifications to the MinHashEncoder and GapEncoder:
handle_missing=""becomeszero_impute, since we actually do not impute missing values with an empty string. Instead we assign them a encoding vector filled with zeros.(N_samples, 1)(to be consistent with scikit-learn), I updated the MinHashEncoder to behave in the same way.handle_missing="zero_impute"becomesempty_impute, since we impute NaN with an empty string"".