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古董Leon

Struct vocab word *vocab; / 词表. Int *vocab hash; / 词hash码对应词下标的数组. Precompute f(x) = x / (x 1). 主要承担初始化、开内存、建Huffman树的任务，为syn0,syn1 采用HS时 ,syn1neg 采用negative时开内存，其中syn0用-0.005 0.005之间的数随机初始化. B = next random % window;. 其中，f是 (σ(neu1 T syn1) ). P(x) = frac{exp(neu1[c] * syn1[c l2])}{(1 exp(neu1[c] * syn1[c l2]) }$. Log(L) = code[d]* neu1[c] * syn1[c l2] (1-code[d])*log(1 exp(neu1[c] * syn1[c l2]) $. Frac{( log(L) }{ syn1}= (1 -code - p(x) *neu1$. Neu1e= frac{( log(L) }{ neu1}= (1 -code - p(x) *syn1$.

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古董Leon | liustrive.com Reviews

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Struct vocab word *vocab; / 词表. Int *vocab hash; / 词hash码对应词下标的数组. Precompute f(x) = x / (x 1). 主要承担初始化、开内存、建Huffman树的任务，为syn0,syn1 采用HS时 ,syn1neg 采用negative时开内存，其中syn0用-0.005 0.005之间的数随机初始化. B = next random % window;. 其中，f是 (σ(neu1 T syn1) ). P(x) = frac{exp(neu1[c] * syn1[c l2])}{(1 exp(neu1[c] * syn1[c l2]) }$. Log(L) = code[d]* neu1[c] * syn1[c l2] (1-code[d])*log(1 exp(neu1[c] * syn1[c l2]) $. Frac{( log(L) }{ syn1}= (1 -code - p(x) *neu1$. Neu1e= frac{( log(L) }{ neu1}= (1 -code - p(x) *syn1$.

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1 古董leon

2 word2vec code 阅读笔记

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古董leon,word2vec code 阅读笔记,via liustrive com,negative,binary,cbow,debug mode,window,min count,num threads,min reduce,window是训练时前后文长度随机数的边界，其它参数看名字,layer1 size,向量维度,基本词结构体,struct,vocab word,long,point,root 到该节点的路径，存的是路径节点索引,char,word,code,huffman编码,codelen

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古董Leon | liustrive.com Reviews

https://liustrive.com

Struct vocab word *vocab; / 词表. Int *vocab hash; / 词hash码对应词下标的数组. Precompute f(x) = x / (x 1). 主要承担初始化、开内存、建Huffman树的任务，为syn0,syn1 采用HS时 ,syn1neg 采用negative时开内存，其中syn0用-0.005 0.005之间的数随机初始化. B = next random % window;. 其中，f是 (σ(neu1 T syn1) ). P(x) = frac{exp(neu1[c] * syn1[c l2])}{(1 exp(neu1[c] * syn1[c l2]) }$. Log(L) = code[d]* neu1[c] * syn1[c l2] (1-code[d])*log(1 exp(neu1[c] * syn1[c l2]) $. Frac{( log(L) }{ syn1}= (1 -code - p(x) *neu1$. Neu1e= frac{( log(L) }{ neu1}= (1 -code - p(x) *syn1$.

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Struct vocab word *vocab; / 词表. Int *vocab hash; / 词hash码对应词下标的数组. Precompute f(x) = x / (x 1). 主要承担初始化、开内存、建Huffman树的任务，为syn0,syn1 采用HS时 ,syn1neg 采用negative时开内存，其中syn0用-0.005 0.005之间的数随机初始化. B = next random % window;. 其中，f是 (σ(neu1 T syn1) ). P(x) = frac{exp(neu1[c] * syn1[c l2])}{(1 exp(neu1[c] * syn1[c l2]) }$. Log(L) = code[d]* neu1[c] * syn1[c l2] (1-code[d])*log(1 exp(neu1[c] * syn1[c l2]) $. Frac{( log(L) }{ syn1}= (1 -code - p(x) *neu1$. Neu1e= frac{( log(L) }{ neu1}= (1 -code - p(x) *syn1$.

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