trueskill

trueskill: Implementation the TrueSkill algorithm in R. An implementation of the TrueSkill algorithm (Herbrich, R., Minka, T. and Grapel, T) in R; a Bayesian skill rating system with inference by approximate message passing on a factor graph. Used by Xbox to rank gamers and identify appropriate matches. http://research.microsoft.com/en-us/projects/trueskill/default.aspx Current version allows for one player per team. Will update as time permits. Requires R version 3.0 as it is written with Reference Classes. URL: https://github.com/bhoung/trueskill-in-r Acknowledgements to Doug Zongker and Heungsub Lee for their python implementations of the algorithm and for the liberal reuse of Doug’s code comments (@dougz and @sublee on github).


References in zbMATH (referenced in 11 articles )

Showing results 1 to 11 of 11.
Sorted by year (citations)

  1. Shah, Nihar B.; Balakrishnan, Sivaraman; Bradley, Joseph; Parekh, Abhay; Ramchandran, Kannan; Wainwright, Martin J.: Estimation from pairwise comparisons: sharp minimax bounds with topology dependence (2016)
  2. Gordon, Andrew D.; Graepel, Thore; Rolland, Nicolas; Russo, Claudio; Borgstrom, Johannes; Guiver, John: Tabular, a schema-driven probabilistic programming language (2014)
  3. Gordon, Andrew D.; Aizatulin, Mihhail; Borgstrom, Johannes; Claret, Guillaume; Graepel, Thore; Nori, Aditya V.; Rajamani, Sriram K.; Russo, Claudio: A model-learner pattern for Bayesian reasoning (2013)
  4. Balakrishnan, Suhrid; Chopra, Sumit: Two of a kind or the ratings game? Adaptive pairwise preferences and latent factor models (2012)
  5. Huang, Jim C.; Frey, Brendan J.: Cumulative distribution networks and the derivative-sum-product algorithm: models and inference for cumulative distribution functions on graphs (2011)
  6. Weng, Ruby C.; Lin, Chih-Jen: A Bayesian approximation method for online ranking (2011)
  7. Pahikkala, Tapio; Waegeman, Willem; Tsivtsivadze, Evgeni; Salakoski, Tapio; de Baets, Bernard: Learning intransitive reciprocal relations with kernel methods (2010)
  8. Waegeman, Willem; De Baets, Bernard; Boullart, Luc: Kernel-based learning methods for preference aggregation (2009)
  9. Coulom, Rémi: Whole-history rating: A Bayesian rating system for players of time-varying strength (2008)
  10. Glickman, Mark E.: Bayesian locally optimal design of knockout tournaments (2008)
  11. Waegeman, Willem; De Baets, Bernard; Boullart, Luc: Learning layered ranking functions with structured support vector machines (2008)