损失函数，mse，cee

import numpy as np


# mse,rmse == sqrt(mse) 均方差
def mse(y, t):
    return 0.5 * np.sum((y - t)**2)


# cross entropy error
def cee(y, t):
    return -np.sum(t * np.log(y + 1e-7))  # 1e7防止log(0)出现


y = np.array([0.1, 0.2, 0.6, 0.1])  # 模拟神经网络输出
t = np.array([0, 0, 0, 1])  # one-hot表示

print("y:", y, "t", t)
r = mse(y, t)
print("mse:", r)    # 结果越小越准确
r = cee(y, t)
print("cee:", r)    # 结果越接近1越准确