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PySS3 supports interpretable text classification with SS3 and visualization tools for explainable AI.
About PySS3
PySS3 is a Python library for text classification using the SS3 model and the t-SS3 variant, which recognizes variable-length word n-grams during classification. It includes an SS3 classifier with fit, predict, single-label and multilabel methods, plus an extract_insight method that returns text fragments involved in a decision. The library also provides a Live_Test component for browser-based model testing and an Evaluation component for hyperparameter grid search with history tracking and 3D plots exportable as HTML.
Key features
- SS3 classifier with fit and predict methods following sklearn style
- extract_insight returns text fragments involved in classification decision
- Multilabel classification support through classify_multilabel method
- Browser-based interactive model testing with Live_Test.run
- Hyperparameter grid search with k-fold evaluation support
- Interactive 3D hyperparameter plots exportable as HTML
Best for: Python developers and researchers who need text classification with visible decision rationale.
Good for
- Open source Python library installable with pip install pyss3
- Returns text fragments behind predictions for inspection
- Includes interactive testing and hyperparameter visualization tools
PySS3 at a glance
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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PySS3 FAQ
How do I install PySS3?
Install with pip install pyss3.
How can I see why the model made a decision?
Use extract_insight(), which returns a list of text fragments involved in the classification decision.
How do I test a trained model interactively?
Use Live_Test.run(clf, x_test, y_test) from pyss3.server to test the model in a browser.
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