e8f02e56f356dfecd5d7bb271f2fa54deb71ee00,tests/meta/test_adaptive_random_forest_regressor.py,,test_adaptive_random_forest_regressor_drift_detection_coverage,#,139

Before Change

                y = np.asarray([np.random.normal(loc=-5, scale=1.0)])
        elif cnt < 500:  // First abrupt drift
            if np.sum(x) > threshold:
                y = np.asarray([np.random.normal(loc=10, scale=1.0)])
            else:
                y = np.asarray([np.random.normal(loc=-10, scale=1.0)])
        else:  // Second abrupt drift

After Change

    error1 = mean_absolute_error(y_true, y_pred1)
    error2 = mean_absolute_error(y_true, y_pred2)

    assert np.isclose(round(error1, 2), expected_error1)
    assert np.isclose(round(error2, 2), expected_error2)

Instances