The Rich Get Richer: Disparate Impact of Semi-Supervised Learning

Overview

The Rich Get Richer:
Disparate Impact of Semi-Supervised Learning

Preprocess file of the dataset used in implicit sub-populations:
(Demographic groups: race and gender)

The following code will pre-process the jigsaw dataset and return train/test dataset files including demographic groups information.

Step-1:

Download the jigsaw dataset: identity_individual_annotations.csv from

https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification/data.

Step-2:

python preprocecss_jiasaw_toxicity_gender_and_race_balanced.py

Implementation of SSL methods

Please follow the official implementations of MixMatch, MixText, and UDA.

[1] https://github.com/google-research/mixmatch

[2] https://github.com/GT-SALT/MixText

[3] https://github.com/google-research/uda

Owner
[email protected]
REsponsible & Accountable Learning (REAL) @ University of California, Santa Cruz
<a href=[email protected]">
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