Project details for choix

Logo choix 0.3.1

by lum - February 12, 2018, 14:47:04 CET [ Project Homepage BibTeX Download ]

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choix is a Python library that provides inference algorithms for models based on Luce's choice axiom. These probabilistic models can be used to explain and predict outcomes of comparisons between items.

  • Pairwise comparisons: when the data consists of comparisons between two items, the model variant is usually referred to as the Bradley-Terry model. It is closely related to the Elo rating system used to rank chess players.
  • Partial rankings: when the data consists of rankings over (a subset of) the items, the model variant is usually referred to as the Plackett-Luce model.
  • Top-1 lists: another variation of the model arises when the data consists of discrete choices, i.e., we observe the selection of one item out of a subset of items.
  • Choices in a network: when the data consists of counts of the number of visits to each node in a network, the model is known as the Network Choice Model.

choix makes it easy to infer model parameters from these different types of data, using a variety of algorithms:

  • Luce Spectral Ranking
  • Minorization-Maximization
  • Rank Centrality
  • Approximate Bayesian inference with expectation propagation
Changes to previous version:

Initial Announcement on

BibTeX Entry: Download
Supported Operating Systems: Any
Data Formats: Not Applicable
Tags: Python, Choice, Comparisons, Preferences, Rankings
Archive: download here


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