opennlp/Large-Scale-Text-Classification

Large Scale benchmarking of state of the art text vectorizers

42
/ 100
Emerging

This project helps data scientists and machine learning engineers understand the best way to prepare text data for classification tasks. It takes raw text datasets and different text 'vectorization' methods as inputs, then shows how accurately each method performs on tasks like sentiment analysis or spam detection. The output is a clear comparison of which text preparation techniques work best across many different types of text data.

Use this if you need to choose an effective method to convert text into a numerical format for machine learning, especially for text classification problems.

Not ideal if you are looking for a pre-built solution to directly classify text without needing to compare different data preparation techniques.

text-classification natural-language-processing machine-learning-engineering data-science text-analytics
No Package No Dependents
Maintenance 13 / 25
Adoption 4 / 25
Maturity 16 / 25
Community 9 / 25

How are scores calculated?

Stars

7

Forks

1

Language

Python

License

Apache-2.0

Last pushed

Mar 18, 2026

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/nlp/opennlp/Large-Scale-Text-Classification"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.