吴裕雄 python 机器学习——模型选择回归问题性能度量

from sklearn.metrics import mean_absolute_error,mean_squared_error

#模型选择回归问题性能度量mean_absolute_error模型
def test_mean_absolute_error():
    y_true=[1,1,1,1,1,2,2,2,0,0]
    y_pred=[0,0,0,1,1,1,0,0,0,0]
    print("Mean Absolute Error:",mean_absolute_error(y_true,y_pred))
    
#调用test_mean_absolute_error()
test_mean_absolute_error()

#模型选择回归问题性能度量mean_squared_error模型
def test_mean_squared_error():
    y_true=[1,1,1,1,1,2,2,2,0,0]
    y_pred=[0,0,0,1,1,1,0,0,0,0]
    print("Mean Absolute Error:",mean_absolute_error(y_true,y_pred))
    print("Mean Square Error:",mean_squared_error(y_true,y_pred))
    
#调用test_mean_squared_error()
test_mean_squared_error()