cfg.yaml

data_cfg_path: '../data/dataset_cfg.yaml'
dataset_path: '../data/preprocessed.parquet'
destination_path: './expert_team/'

fitting_set: [0,20000]

baseline_group: 'standard'

# In dataset.cfg we defined the protected classes as ["sex", "binarized_race", "age"]

experts:
  groups:
    standard:
      n: 5
      group_seed: 0
      w_mean: 0
      w_stdev: 0.5
      theta: 1
      protected_mean:
        - 0
        - 0
        - 0
      protected_stdev: 
        - 0
        - 0
        - 0
      alpha_mean: 20
      alpha_stdev: 5
      fpr:
        target_mean: 0.15
        target_stdev: 0.03
      fnr:
        target_mean: 0.15
        target_stdev: 0.03
      max_FPR: 1
      min_FPR: 0.01
      max_FNR: 1
      min_FNR: 0.01
    biased_vs_females:
      n: 5
      group_seed: 1
      protected_mean:
        - -1
        - 0
        - 0
      protected_stdev: 
        - 0.1
        - 0
        - 0
    biased_vs_non_white:
      n: 5
      group_seed: 2
      protected_mean:
        - 0
        - -1
        - 0
      protected_stdev: 
        - 0
        - 0.1
        - 0
    biased_vs_older:
      n: 5
      group_seed: 3
      protected_mean:
        - 0
        - 0
        - -1
      protected_stdev: 
        - 0
        - 0
        - 0.1
    sparse-dependency:
      n: 5
      group_seed: 4
      theta: 0.5