Python fbeta_scoreの例

コード例 #1

ファイル: test_metrics.py プロジェクト: MarcBS/keras

def test_fbeta_score():
    y_true = K.variable(np.array([0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0]))
    y_pred = K.variable(np.array([1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0]))

    # Calculated using sklearn.metrics.f1_score
    expected = 0.33333333333333331

    actual = K.eval(metrics.fbeta_score(y_true, y_pred))
    epsilon = 1e-05
    assert expected - epsilon <= actual <= expected + epsilon

コード例 #2

def test_fbeta_score():
    y_true = K.variable(np.array([0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0]))
    y_pred = K.variable(np.array([1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0]))

    # Calculated using sklearn.metrics.fbeta_score
    expected = 0.30303030303030304

    actual = K.eval(metrics.fbeta_score(y_true, y_pred, beta=2))
    epsilon = 1e-05
    assert expected - epsilon <= actual <= expected + epsilon