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One Hot Encoder: Drop one redundant feature by default for features with two categories #1993

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@angela97lin angela97lin commented Mar 17, 2021

Closes #1936. Uses scikit-learn impl. Does not always select minority class, see #1936 (comment) as to why this is challenging :'(

I also have my branch 1936_ohe where I was testing out impl for minority class before hitting the error if anyone is curious.

Useful for parameters defaults: #830

If drop == 'is_binary' and 'handle_unknown' == 'ignore', scikit-learn raises an error.

@angela97lin angela97lin marked this pull request as ready for review March 17, 2021 21:21
@angela97lin angela97lin marked this pull request as draft March 17, 2021 21:22
@freddyaboulton freddyaboulton deleted the 1936_ohe_simple branch May 13, 2022 15:01
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One Hot Encoder: Drop one redundant feature by default for features with two categories
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