softmax 函数

https://blog.csdn.net/m0_37769093/article/details/107732606

softmax 函数如下所示:

y i = exp ⁡ ( x i ) ∑ j = 1 n exp ⁡ ( x j ) y_{i} = \frac{\exp(x_{i})}{\sum_{j=1}^{n}{\exp(x_j)}} yi=j=1nexp(xj)exp(xi)

softmax求导如下:

i = j i = j i=j 的情况:

∂ y i ∂ x i = exp ⁡ ( x i ) ∑ j = 1 n exp ⁡ ( x j ) − ( exp ⁡ ( x i ) ) 2 ( ∑ j = 1 n exp ⁡ ( x j ) ) 2 \frac{\partial y_{i}}{\partial x_{i}} = \frac{\exp(x_{i})}{\sum_{j=1}^{n}{\exp(x_j)}} - \frac{(\exp(x_{i}))^2}{(\sum_{j=1}^{n}{\exp(x_j)})^2} xiyi=j=1nexp(xj)exp(xi)(j=1nexp(xj))2(exp(xi))2
∂ y i ∂ x i = y i − ( y i ) 2 \frac{\partial y_{i}}{\partial x_{i}} = y_{i} - (y_{i})^2 xiyi=yi(yi)2

i ≠ j i \neq j i=j 的情况:

∂ y i ∂ x j = − ( exp ⁡ ( x i ) × exp ⁡ ( x j ) ) ( ∑ j = 1 n exp ⁡ ( x j ) ) 2 \frac{\partial y_{i}}{\partial x_{j}} = - \frac{(\exp(x_{i})\times\exp(x_{j}))}{(\sum_{j=1}^{n}{\exp(x_j)})^2} xjyi=(j=1nexp(xj))2(exp(xi)×exp(xj))
∂ y i ∂ x j = − y i y j \frac{\partial y_{i}}{\partial x_{j}} = - y_{i}y_{j} xjyi=yiyj

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