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。
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。
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.
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