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()