Badr

Badr

__init__(dset: Dataset, model: Model, metric: FairnessMetric, train_test: str = 'train', oracle: str = 'implicit', solver_cls=None, solver_kwargs=None) -> None

Parameters:

• dset (Dataset) –

  Dataset with (X_train, y_train), (X_test, y_test), and groups.

• model (Model) –

  Model with set_group_weights(...), fit(...), and coef_/intercept_.

• metric (FairnessMetric) –

  Metric; bound to model if metric.model is None.

• train_test ((train, test), default: "train" ) –

  Which split to use.

• oracle ((implicit, stochastic), default: "implicit" ) –

  Oracle implementation to use.

• solver_cls (type, default: None ) –

  Solver class (default: SLSQP).

• solver_kwargs (dict, default: None ) –

  Keyword args passed to solver_cls(...).

Raises:

• ValueError –

  If oracle is not one of {"implicit", "stochastic"}.

run(**run_kwargs) -> None

Run the solver, set group weights, refit the model, and compute outputs.

Parameters:

• **run_kwargs –

  Passed to solver.run(**run_kwargs).

Sets Attributes

group_weights Learned group weights. coef_ Fitted coefficients. intercept_ Fitted intercept. fairness Metric value on the selected split. group_losses Per-group losses from the model.

set_solver(solver)

Set a solver instance to use in run.

Parameters:

• solver –

  Solver instance. If solver.oracle is None, run will set it.

Returns:

• Badr –

  Self.