ModSSC/ModSSC
ModSSC: A Modular Framework for Semi Supervised Classification
This project helps academic researchers and machine learning practitioners categorize data when only a small portion is labeled. It takes in various types of data, like text, images, or sensor readings, and outputs classifications even with limited initial tagging. Researchers can use this to develop and test new methods for efficiently classifying diverse datasets.
Available on PyPI.
Use this if you are an academic researcher focusing on semi-supervised classification and need a flexible, reproducible framework to experiment with new methods across different data types.
Not ideal if you are looking for a plug-and-play solution for immediate, production-ready data classification without interest in algorithm research or customization.
Stars
32
Forks
7
Language
Python
License
MIT
Category
Last pushed
Mar 11, 2026
Commits (30d)
0
Dependencies
4
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