求助啊,李航的最大熵推导是怎么推的?

L ( P , w ) H ( P ) + w 0 ( 1 y P ( y x ) ) + i = 1 n w i ( E p ( f i ) E P ( f i ) ) = x , y P ~ ( x ) P ( y x ) log P ( y x ) + w 0 ( 1 y P ( y x ) ) + i = 1 n w i ( x , y P ~ ( x , y ) f i ( x , y ) x , y P ~ ( x ) P ( y x ) f i ( x , y ) ) \begin{aligned} L(P, w) & \equiv-H(P)+w_{0}\left(1-\sum_{y} P(y | x)\right)+\sum_{i=1}^{n} w_{i}\left(E_{\overline{p}}\left(f_{i}\right)-E_{P}\left(f_{i}\right)\right) \\=& {\color{red}\sum_{x, y} \tilde{P}(x) P(y | x) \log P(y | x) } +{\color{blue} w_{0}\left(1-\sum_{y} P(y | x)\right)} \\ &+\sum_{i=1}^{n} w_{i}\left(\sum_{x, y} \tilde{P}(x, y) f_{i}(x, y)-\sum_{x, y} \tilde{P}(x) P(y | x) f_{i}(x, y)\right) \end{aligned}

L ( P , w ) L(P, w) 对P(y|x)求导 假如是对 P ( y 1 x 1 ) P(y_1|x_1) 求导,如下

L ( P , W ) P ( y 1 x 1 ) = P ~ ( x 1 ) ( l o g P ( y 1 x 1 ) + 1 ) w 0 + i = 1 n w i x , y P ~ ( x ) P ( y x ) f i ( x , y ) \frac{\partial L(P,W)}{\partial P(y_1|x_1)}={\color{red}\tilde {P}(x_1)(logP(y_1|x_1)+1)}{\color{blue}-w_0}+\sum_{i=1}^nw_i\sum_{x,y}\tilde P(x)P(y|x)f_i(x,y)

其中红色部分是因为只有 x = x 1 , y = y 1 x=x_1,y=y_1 那一项才含有 P ( y 1 x 1 ) P(y_1|x_1)

应用 x P ~ ( x ) = 1 \sum_x\tilde P(x)=1
= P ~ ( x 1 ) ( l o g P ( y 1 x 1 ) + 1 ) + x P ~ ( x ) w 0 + x , y P ~ ( x ) i = 1 n w i P ( y x ) f i ( x , y ) =\tilde{P}(x_1)(logP(y_1|x_1)+1) +\sum_x\tilde P(x)w_0+\sum_{x,y}\tilde P(x)\sum_{i=1}^nw_iP(y|x)f_i(x,y)

问题是最后怎么推出
x , y P ~ ( x ) ( log P ( y x ) + 1 w 0 i = 1 n w i f i ( x , y ) ) \sum_{x, y} \tilde{P}(x)\left(\log P(y | x)+1-w_{0}-\sum_{i=1}^{n} w_{i} f_{i}(x, y)\right)
的???

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转载自blog.csdn.net/eruiwen1624/article/details/89336821