sergioburdisso/pyss3
A Python library for Interpretable Machine Learning in Text Classification using the SS3 model, with easy-to-use visualization tools for Explainable AI :octocat:
This tool helps researchers, analysts, and content moderators understand why their text classification models make certain decisions. You input text data with associated categories, and it outputs predictions along with clear explanations of how those predictions were reached. It's designed for anyone who needs transparent and justifiable insights from their text analysis.
349 stars. Available on PyPI.
Use this if you need to classify text into categories and, more importantly, understand the specific words or phrases that led your model to its conclusions.
Not ideal if your primary goal is simply to achieve the highest possible accuracy without needing to interpret the model's inner workings.
Stars
349
Forks
44
Language
Python
License
MIT
Last pushed
Oct 16, 2025
Commits (30d)
0
Dependencies
7
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