lucasmaystre/choix
Inference algorithms for models based on Luce's choice axiom
This project helps you understand preferences and rankings from various types of comparison data. It takes inputs like head-to-head match outcomes, partial rankings, or selections from a list, and outputs a ranked list of items or numerical scores indicating their relative strength. This is for anyone who needs to rank items, products, or entities based on observed choices or comparisons.
189 stars. Used by 3 other packages. No commits in the last 6 months. Available on PyPI.
Use this if you have data from comparisons (like 'Item A was chosen over Item B'), partial rankings (like 'A > B > C'), or top choices from a group, and you need to infer an overall ranking or preference strength for all items involved.
Not ideal if your ranking problem doesn't involve comparative data or discrete choices, or if you need to build predictive models that go beyond simple preference scores.
Stars
189
Forks
31
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Sep 05, 2025
Commits (30d)
0
Dependencies
2
Reverse dependents
3
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