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📺 Using various collaborative filtering and matrix factorisation methods to predict user ratings for the Netflix dataset

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alt text

Abstract

The surprise package was used for this exercise since that allowed for much faster calculations. The methodology for this question was inspired from (Jahrer, Töscher and Legenstein, 2010). The picture below briefly explains the methodology that was adopted for this part of the question. Some essential details missing from the picture below include:

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  • The eight algorithms were trained on the whole training set for the final predictions which would be blended.
  • The blender was trained on the full probe set after recording the rmse. This was only done after the model was selected

License

GNU GENERAL PUBLIC LICENSE

Version 3, 29 June 2007

Copyright (C) 2007 Free Software Foundation, Inc. http://fsf.org/ Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed.

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📺 Using various collaborative filtering and matrix factorisation methods to predict user ratings for the Netflix dataset

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