SA_Classification

Multi Label Classification of short Texts of Science Association
(多标签文本分类，短文本分类 LSTM)

环境安装 (environment)

• python 3.7.10
• tensorflow 1.15.0
• kares 2.2.4
• gensim 3.8.3
• pands 1.2.4
• pydot 1.4.1
• tqdm 4.59.0
• scikit-learn 0.24.1

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使用说明 (Instructions)

运行

python37 train.py

输出

• word2vec output dir
  out/data/embedings
• Train model output
  out/data/model
• Data set preprocessing
  out/data/multi_label

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参考/感谢 (Thanks)

• yongzhuo:Keras-TextClassification
• Convolutional Neural Networks for Sentence Classification
• A Sensitivity Analysis of (and Practitioners’ Guide to) Convolutional Neural Networks for Sentence Classification

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Reference

For citing this work, you can refer to the present GitHub project. For example, with BibTeX:

@misc{SA_Classification,
    howpublished = {\url{https://github.com/atom/SA_Classification}},
    title = {SA_Classification},
    author = {Xiaolong Liu},
    publisher = {GitHub},
    year = {2021}
}