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 文章提出了一种文本分类任务中数据增强的方法：EDA，EDA中包括四种操作，SR、RI、 RS、RD。 实验显示，在五个通用的文本分类数据集上，使用EDA方法增强语料，模型都有一定性能上的提升。 尤其在语料不足
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相关文章
- 1. EDA: Easy Data Augmentation Techniques for Boosting Performance onText Classification Tasks
- 2. NLP论文笔记:Easy Data Augmentation Techniques for Boosting Performance on Text Classification Task
- 3. NLP 数据增强 Data Augmentation
- 4. （转）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