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TrueSkill machine learning samples updated for F# CTP and units of measure

Ralf Herbrich has updated both the TrueSkill in F# and TrueSkill Through Time samples to both work with the new F# September 2008 CTP and to use unit-of-measure with the Gaussian belief distributions.

 

Ralf says:

Following the publication of the F# source code for the TrueSkill Through Time paper, we have used the same inference library code to demonstrate how the original TrueSkill algorithm can be coded. In the attached source code, only the program.fs file is different to the TrueSkill through Time blog post and it builds up the factor graph for an arbitrary N-player game with an arbitrary draw probability. Both these numbers can be entered on the command line when running the resulting sample. We tried to make sure to stay as close as possible to the description on page 3 of the TrueSkill technical report.

The performance is the same (i.e. excellent), and the code reads a lot better, Using units of measure there is very little chance to mix standard deviations and variances.

Published Monday, September 22, 2008 1:18 AM by dsyme

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# TrueSkill machine learning samples updated for F# CTP and units of measure : EasyCoded

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