How to use the fairlearn.metrics.mean_prediction function in fairlearn

To help you get started, we’ve selected a few fairlearn examples, based on popular ways it is used in public projects.

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github fairlearn / fairlearn / test / unit / metrics / test_mean_predictions.py View on Github external
def test_mean_prediction_unweighted():
    y_pred = [0, 1, 2, 3, 4]
    y_true = None

    result = metrics.mean_prediction(y_true, y_pred)

    assert result == 2
github fairlearn / fairlearn / test / unit / metrics / test_mean_predictions.py View on Github external
def test_mean_prediction_single():
    y_pred = [42]
    y_true = None

    result = metrics.mean_prediction(y_true, y_pred)

    assert result == 42
github fairlearn / fairlearn / test / unit / metrics / test_mean_predictions.py View on Github external
def test_mean_prediction_weighted_single():
    y_pred = [42]
    y_true = None
    weight = [2]

    result = metrics.mean_prediction(y_true, y_pred, weight)

    assert result == 42
github fairlearn / fairlearn / test / unit / metrics / test_mean_predictions.py View on Github external
def test_mean_prediction_weighted():
    y_pred = [0, 1, 2, 3, 4]
    y_true = None
    weight = [8, 2, 1, 2, 1]

    result = metrics.mean_prediction(y_true, y_pred, weight)

    assert result == 1