EDA Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks
EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks 概述 文章提出了一種文本分類任務中數據增強的方法：EDA，EDA中包括四種操作，SR、RI、 RS、RD。 實驗顯示，在五個通用的文本分類數據集上，使用EDA方法增強語料，模型都有一定性能上的提升。 尤其在語料不足
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- 1. EDA: Easy Data Augmentation Techniques for Boosting Performance onText Classification Tasks
- 2. NLP論文筆記:Easy Data Augmentation Techniques for Boosting Performance on Text Classification Task
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- 9. Very Deep Convolutional Networks for Text Classification
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相關文章
- 1. EDA: Easy Data Augmentation Techniques for Boosting Performance onText Classification Tasks
- 2. NLP論文筆記:Easy Data Augmentation Techniques for Boosting Performance on Text Classification Task
- 3. NLP 數據增強 Data Augmentation
- 4. （轉）AutoML for Data Augmentation
- 5. data augmentation - image augmentation - imgaug
- 6. BERT for unsupervised text tasks
- 7. Data Augmentation by Pairing Samples for Images Classification
- 8. Understanding data augmentation for classification: when to warp?
- 9. Very Deep Convolutional Networks for Text Classification
- 10. WS-DAN:Weakly Supervised Data Augmentation Netowrk for Fine-Grained Visual Classification