neural-network - 为什么神经网络损失函数总是正的

Question

我正在努力填补我的知识空白。在查看神经网络的大多数损失函数时，例如 mse、mae、L1、L2，损失总是记录为正值。我不明白的是为什么？为了根据需要提高或降低网络的权重，损失函数不应该具有正值或负值吗？

Answer 1

像均方误差 (MSE) 函数这样的损失函数总是给出正损失值。他们倾向于显示错误有多大而不是在哪里发生的错误。

Suppose our Neural Network is a basketball player. Its task is to throw the ball in the basket. If the ball falls to the left of the basket, the error is negative. But, if it falls to the right, the error is positive. If it falls in the basket, the error is 0. This approach was followed by earlier loss functions. In this case, MSE gives a positive loss and gives the loss regarding that the ball has not reached the basket. It does not bother about whether the ball fell to the right or left of the basket.