zhaominyiz/EPiDA
Official Code for 'EPiDA: An Easy Plug-in Data Augmentation Framework for High Performance Text Classification' - NAACL 2022
This framework helps machine learning practitioners improve the accuracy of text classification models, especially when working with limited labeled data. It takes your existing text datasets and generates additional, similar text examples, resulting in a more robust and accurate classification model. Data scientists and AI researchers focused on natural language processing would find this useful for enhancing their text-based machine learning projects.
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Use this if you need to train a high-performing text classifier but have a small or imbalanced dataset, and you want to artificially expand your training data to achieve better results.
Not ideal if your primary goal is to interpret the linguistic features of your text or if you have an abundance of labeled data, making augmentation unnecessary.
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23
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2
Language
Python
License
Apache-2.0
Category
Last pushed
May 09, 2022
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