alessandro1802 / analysis-of-fairness-measures Goto Github PK

y = count, x = FM on 0.01, 0.1, 0.5 ... for FM: MinR. GR, SB ... (test e.g equality of % of hires of group1 and group2)

1. play with the number of bins
2. normalize y axis to probabilities tricky
3. find where NULLs occur while computing FMs, count them, keep them out of hists (plot aside) very tricky

1. Move functions to a separate utils.py and use importing it.
2. Come up with more tests.
3. Add requirements.txt.

For a given n generate all possible binary group confusion matrices, e.g for n = 10

Write the goal of the project, mention original repo, add environment set up tutorial.

Check if the the data is generated correctly. GR measure may be used.

Precess dataset with appropriate names.
Create functions for computing, make plots (MinR, GR, SB ...).

Fix var names, last plots.

1. Populate calculations dir with computation for smaller n as an example.
2. Come up with a way of storing and accessing the main data remotely.