...
|  |  |
|---|---|---|
| cumulative #of_instances per group in 10 boosting rounds | 4 groups weights per boosting rounds | 6 group weights per boosting round |
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Protected groups augmentation (protected positives and protected negatives)
|
|
|  |
|---|---|---|---|
| adult 10%- 20 boosting rounds | adult 10%- 20 boosting rounds | compa- race 10%- 20 boosting rounds | compas - gender 10%- 20 boosting rounds |
for datasets with less imbalance this seems to be better. compare the results above. It is obvious that by augmenting protected negatives (TNR) increases but not just for the protected subgroup of instances but also for the non-protected group. compare the results with the ones below where we smote based on minority class
 |
|  |  |
|---|---|---|---|
| adult 10%- 100 boosting rounds | adult 10%- 100 boosting rounds | compa- race 10%- 100 boosting rounds | compas - gender 10%- 100 boosting rounds |
