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Enhance treatment of missing value in one-hot encoder

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#47 10 comments 0 reactions 0 assignees View on GitHub

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Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
25/100
Issue type
Feature
Clarity
Needs clarification
Activity status
Stale
Tech stack
julia
Domain
machine-learning

Research direction

Start with the OneHotEncoder missing-value handling added in issue #457, then read the discussion linked from MLJModels.jl issue #450. Clarify which popular missing-value options should be supported and how they should behave; done means the agreed options are implemented and their behavior is verified.

Written by the indexing model from the issue text.

Description

There is now missing value handling in OneHotEncoder but this simply propagates the missing values. I guess it might be nice to offer some other popular options for handling missing values which might be complicated to handle in a post-processing step. See also the discussion here.

@Chandu-4444 @Frank-III @OlivierLabayle

Dominant language
Julia
Stars
1
Forks
2
Avg merge
9d 22h
Merged PRs (30d)
2

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