jasonwei20/eda_nlp

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1652 stars · 312 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

EDA (Easy Data Augmentation) is a Python library implementing four simple text augmentation operations—synonym replacement, random insertion, random swap, and random deletion—for boosting text classification performance. It is the official code for an EMNLP 2019 paper and works especially well on small training datasets.

Use cases

• augment a small text classification dataset
• generate synthetic training sentences via synonym replacement
• improve classifier accuracy with limited labeled data
• apply random swap and deletion augmentation to NLP training data
• replicate EMNLP 2019 EDA paper experiments

When to choose

• you have a small text classification dataset (under ~500 examples) and need more training data
• you want lightweight augmentation without training a language model
• you need a simple, well-cited baseline augmentation technique

When to avoid

• you need augmentation for languages other than English without extra work
• you want context-aware or LLM-based paraphrasing quality
• you need a maintained, licensed production dependency (no license, minimal upkeep)

Facets

library · maturity maintenance

nlp data-generation machine-learning machine-learning data-science python cli data-augmentation text-classification synonym-replacement wordnet nltk research-code emnlp-2019 natural-language-processing

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