vault backup: 2024-04-29 18:59:38
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# 熵
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随机变量$X = \{x_1,x_2,...,x_i\}$,对应的概率为$p_i = p(X = x_i)$,则熵为
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$$
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H(X) = - \sum_{i=1}^{n}p(x_i) \log p(x_i)
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$$
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> $p(x_i)=0$时,$p(x_i)logp(x_i)=0$
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# 交叉熵
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$$
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H(p,q) = \sum_x p(x) \frac{1}{q(x)}=-\sum_x p(x) \log q(x)
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$$
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> 表示对预测分布$q(x)$使用真实分布$p(x)$来进行编码时所需要的信息量大小。
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# KL散度
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# KL散度
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