trueskill-package: Implementation of the TrueSkill algorithm

In bhoung/trueskill-in-r: Implementation of the TrueSkill algorithm in R

Description

An R implementation of the TrueSkill Algorithm (Herbrich, R., Minka, T. and Grapel, T. [1]), 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 implemented with Reference Classes.

The code for the examples can be found at:

system.file('', package = 'trueskill')

Acknowledgements to Doug Zongker [2] and Heungsub Lee [3] for their python implementations of the algorithm and for the liberal reuse of Doug's code comments.

Html documentation is at http://www.bhoung.com/trueskill/

Details

Package:	trueskill
URL:	http://www.bhoung.com/trueskill
Version:	0.1
License:	Apache
Depends:	R (>= 3.0)
Built:	R 3.0.1

Main Functions and Classes

Reference Classes:

Gaussian, Player, Parameters

Methods:

Multiply, Divide

Functions:

Trueskill, DrawMargin, DrawProbability, Print

Data:

data

Author(s)

Brendan Houng <[e-mail]>

References

[1]

TrueSkill: A Bayesian Skill Rating System, Herbrich, R., Minka, T. and Grapel, T.

[2]

Doug Zongker's python implementation:
https://github.com/dougz/trueskill

[3]

Heungsub Lee's python implementation:
https://github.com/sublee/trueskill.

[4]

Jeff Moser's explanatory notes:
http://www.moserware.com/2010/03/computing-your-skill.html

Examples

  # Example 1.
  
  # set default values for BETA, EPSILON and GAMMA where BETA is sigma / 2
  # EPSILON is DrawProbability(0.1)
  # GAMMA is sigma / 100
  epsilon <- DrawMargin(draw_probability = 0.1, beta = 25 / 6, num_teams = 4)
  parameters <- Parameters(beta = 25/6, epsilon, 25 / 300)
  
  Alice  <- Player(name = "Alice", skill = Gaussian(mu = 25, sigma = 25 / 3))
  Bob    <- Player(name = "Bob", skill = Gaussian(mu = 25, sigma = 25 / 3))
  Chris  <- Player(name = "Chris", skill = Gaussian(mu = 25, sigma = 25 / 3))
  Darren <- Player(name = "Darren", skill = Gaussian(mu = 25, sigma = 25 / 3)) 
   
  Team1 <- Team(name = "Team Alice", rank = 1, players = list(Alice))
  Team2 <- Team(name = "Team Bob", rank = 2, players = list(Bob))
  Team3 <- Team(name = "Team Chris", rank = 2, players = list(Chris))
  Team4 <- Team(name = "Team Darren", rank = 4, players = list(Darren))

  teams <- list(Team1, Team2, Team3, Team4)
  teams <- Trueskill(teams, parameters) 
  Print(teams)
  
  players <- GetPlayers(teams)
  Print(players)

  Alice <- players[[1]]
  print(Alice$skill) 

  # Example 2 - see https://gist.github.com/bhoung/5596282  
  # the example applies trueskill to tennis tournament data
  # (runtime is approx 50 secs)
  

bhoung/trueskill-in-r documentation built on May 12, 2019, 8:29 p.m.