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用MLP、TextCNN、RNN、LSTM、GRU、Attention、RCNN、BERT做文本分类、情感分析,对比各模型于温泉旅游评论垂类语料下在情感分类任务上的表现

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sentiment-analysis

用MLP、TextCNN、RNN、LSTM、GRU、Attention、RCNN、BERT做文本分类、情感分析,对比各模型于温泉旅游评论垂类语料下在情感分类任务上的表现

简介

框架

  • PyTorch
  • huggingface/transformers
  • scikit-learn
  • pandas
  • Matplotlib
  • synonyms

模型

  • MLP
    • MLP1H
    • MLP2H
    • MLP6H
  • TextCNN
    • TextCNN1d
    • TextCNN2d
  • RNNs
    • Bi-RNN
    • Bi-LSTM
    • Bi-GRU
  • Attention
    • Bi-LSTM+Attention
  • RCNN
  • BERT
    • BERT
    • BERT+TextCNN2d
    • BERT+Bi-LSTM+Attention
    • BERT+RCNN

数据集

训练过程

  • MLP1H, MLP2H, MLP6H

  • TextCNN1d, TextCNN2d

  • Bi-RNN, Bi-LSTM, Bi-GRU

  • Bi-LSTM+Attention, RCNN, Bi-LSTM

  • BERT, BERT+TextCNN2D, BERT+Bi-LSTM+Attention, BERT+RCNN

  • MLP1H, TextCNN1D, Bi-LSTM+Attention, RCNN, BERT

实验结果

参考

https://github.com/jeffery0628/text_classification

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用MLP、TextCNN、RNN、LSTM、GRU、Attention、RCNN、BERT做文本分类、情感分析,对比各模型于温泉旅游评论垂类语料下在情感分类任务上的表现

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  • Python 5.3%