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Embedding + 平均池化
训练本质:通过 loss 反向传播,不断调整词向量表和线性分类器,让平均出来的句子向量越来越容易被正确分到正面或负面。 核心思想:先把每个词变成向量,然后把一句话中所有有效词向量求平均,用这个平均向量代表整句话,再送入全连接层做正负面分类。
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