Details
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New Feature
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Status: Closed
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Major
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Resolution: Fixed
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0.5
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None
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None
Description
Some real-world datasets (especially those created from implicit feedback) might include users with only a tiny number of preferences (like one-time-visitors only viewing a single item) that a users of ItemSimilarityJob or RecommenderJob might want to prune away. I added a new parameter "minPrefsPerUser" that makes those jobs throw out users with less than a given number of preferences. It is per default set to 1 so that the input data stays untouched.
It's just a small patch to make those jobs more usable in real-world scenarios.