Difference between revisions of "MyMediaLite"

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* Twitter: [http://twitter.com/mymedialite @mymedialite]
 
* Twitter: [http://twitter.com/mymedialite @mymedialite]
 
* [http://www.slideshare.net/zenogantner/mymedialite presentation at FOSDEM 2011]
 
* [http://www.slideshare.net/zenogantner/mymedialite presentation at FOSDEM 2011]
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* [http://channel9.msdn.com/coding4fun/blog/MyMediaLite-Recommender-System-Library blog post about MyMediaLite] at MSDN Channel 9's Coding4Fun blog
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* [http://bickson.blogspot.com/2011/11/spotlight-zeno-gantner-mymedialight.html interview about MyMediaLite] at [[Danny Bickson]]'s blog
  
 
[[Category: Software]]
 
[[Category: Software]]

Revision as of 06:38, 15 November 2011

MyMediaLite is a lightweight, multi-purpose library of recommender system algorithms, written in C#. Using Mono, it runs on all major computing platforms.

It addresses the two most common scenarios in collaborative filtering:

MyMediaLite is free software (open source software), it can be used and distributed under the terms of the GNU General Public License (GPL).

All recommender implementations in MyMediaLite are based on the same efficient and scalable infrastructure; for each recommendation task, there is an API and a base class that make it easy to implement new recommenders. Recommenders may use the collaborative data, plus additionally user/item attributes and user/item relations.

MyMediaLite includes evaluation routines for rating prediction and item prediction; it can measure MAE, RMSE, AUC, prec@N, MAP, and NDCG. It also comes with command line tools that expose most of the library's functionality, accepting data in a simple text-based input format compatible to the one used by Mahout.

Additional features:

  • saving and reloading of recommender models
  • real-time online updates for many recommenders
  • attribute-based diversification of recommendation lists

Literature

External links