Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

More options with dataset creation #327

Open
olliethomas opened this issue May 5, 2020 · 0 comments
Open

More options with dataset creation #327

olliethomas opened this issue May 5, 2020 · 0 comments
Labels
enhancement New feature or request

Comments

@olliethomas
Copy link
Member

This paper https://arxiv.org/pdf/1905.12728.pdf landed on arxiv this week. Their main point is that unfair behaviour can occur during data cleaning, in particular how we deal with missing values. They explicitly talk about how every fairness framework out there (they don't mention EthicML) doesn't take this into account.... but we kind of can.

This user story is to put a bit more oomph around it. Maybe we should have the strategies that they suggest as part of the dataset class, i.e.
Adult(missing_data='drop_row'), Adult(missing_data='drop_column') or Adult(missing_data='something_else'), with drop_row being the default (as that's what happens already - I think)

@tmke8 tmke8 added the enhancement New feature or request label Jun 18, 2020
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
enhancement New feature or request
Projects
None yet
Development

No branches or pull requests

2 participants