Skip to content
This repository has been archived by the owner on May 31, 2023. It is now read-only.

Implement "Sampling" fairness-aware preprocessing #12

Open
cosmicBboy opened this issue Aug 30, 2017 · 0 comments
Open

Implement "Sampling" fairness-aware preprocessing #12

cosmicBboy opened this issue Aug 30, 2017 · 0 comments

Comments

@cosmicBboy
Copy link
Owner

Sampling is composed of two methods:

Uniform Sampling

  • uniformly sample (with replacement) n observations from each group, where n is the expected size of that group assuming a uniform distribution (conditioned on the protected class s).

Preferential Sampling

  • sample observations using a ranker R, similar to the massaging method.
  • the procedure is to duplicate the top-ranked X_s1_y+ and X_s0_y– while removing
    top-ranked X_s1_y– and X_s0_y+.
Sign up for free to subscribe to this conversation on GitHub. Already have an account? Sign in.
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant