Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/3098#issuecomment-62468213
That sounds about like what I recall. I should warn that 'precision' is
entirely dependent on a concept of 'relevant' and 'not relevant'
recommendations, which depends on your strategy for holding out data -- recent?
top rated? random? So it is not a universal metric. You're also never really
sure that "non relevant" recommendations are bad. So 14% can be "pretty good".
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