from sklearn.metrics import zero_one_loss,log_loss

def test_zero_one_loss():

    y_true=[1,1,1,1,1,0,0,0,0,0]

    y_pred=[0,0,0,1,1,1,1,1,0,0]

    print("zero_one_loss<fraction>:",zero_one_loss(y_true,y_pred,normalize=True))

    print("zero_one_loss<num>:",zero_one_loss(y_true,y_pred,normalize=False))

test_zero_one_loss()

def test_log_loss():

    y_true=[1, 1, 1, 0, 0, 0]

    y_pred=[[0.1, 0.9],

            [0.2, 0.8],

            [0.3, 0.7],

            [0.7, 0.3],

            [0.8, 0.2],

            [0.9, 0.1]]

    print("log_loss<average>:",log_loss(y_true,y_pred,normalize=True))

    print("log_loss<total>:",log_loss(y_true,y_pred,normalize=False))

test_log_loss()