Obtaining word vectors 获取单词向量
Vector instructions operate on vectors of scalar quantities and on scalar quantities, where the scalar size is byte, halfword, word, and quadword.
矢量指令作用于标量的矢量及标量,其中标量范围为字节、半字、字和四字。
The map workers (in the canonical example) split the work into individual vectors that contain the tokenized word and an initial value (1, in this case).
map 工作线程(在规范的示例中)将工作分割成包含已标记单词和初始值(在此情况下是 1)的单个矢量。
We adopt a way of attribute selection based on word entropy, use vectors which are represented by word frequency, and deduce its corresponding Bayesian formula.
我们采用了基于词熵的特征项提取方法,并且使用特征项单词出现频率来表示向量,推导出相应的贝叶斯计算公式。
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