Add a missing indicator to encode 'missingness' as a feature

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When imputing missing values, you can preserve info about which values were missing and use THAT as a feature!

Why? Sometimes there's a relationship between "missingness" and the target/label you are trying to predict.

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If you liked this video, watch out for tip 11 (coming out next week) in which I explain two other scikit-learn imputers, KNNImputer and IterativeImputer!

dataschool
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That was a great addition to DS tool kit.Thanks for your contribution .

jaikishank
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Great as always. keep up the good work Thanks Mark!

da_ta
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I encountered a problem when i added this ...add_indicator=True...
Inside a working (good) pipeline. After adding this indicator my entire pipeline failed. Any recommendations what to change in pipeline so the addition (of the above) will not compromise the pipeline?

RA-svbv
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