# AutoGluon Predictor constructor arguments
# - see https://github.com/awslabs/autogluon/blob/ef3a5312dc2eaa0c6afde042d671860ac42cbafb/tabular/src/autogluon/tabular/predictor/predictor.py#L51-L159
ag_predictor_args:
  eval_metric: roc_auc
  label: fraud

# AutoGluon Predictor.fit arguments
# - see https://github.com/awslabs/autogluon/blob/ef3a5312dc2eaa0c6afde042d671860ac42cbafb/tabular/src/autogluon/tabular/predictor/predictor.py#L280-L651
ag_fit_args:
  hyperparameters:
#     GBM:
#       num_boost_round: 20
#     NN:
#       num_epochs: 2
  presets: "medium_quality_faster_train"
  num_bag_folds: 2
  num_bag_sets: 1
  num_stack_levels: 0

output_prediction_format: csv  # predictions output format: csv or parquet
feature_importance: true       # calculate and save feature importance if true
leaderboard: true              # save leaderboard output if true