Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/11186#discussion_r52976861
--- Diff: python/pyspark/mllib/recommendation.py ---
@@ -234,11 +238,35 @@ def _prepare(cls, ratings):
def train(cls, ratings, rank, iterations=5, lambda_=0.01, blocks=-1,
nonnegative=False,
seed=None):
"""
- Train a matrix factorization model given an RDD of ratings given
by users to some products,
- in the form of (userID, productID, rating) pairs. We approximate
the ratings matrix as the
- product of two lower-rank matrices of a given rank (number of
features). To solve for these
- features, we run a given number of iterations of ALS. This is done
using a level of
- parallelism given by `blocks`.
+ Train a matrix factorization model given an RDD of ratings given by
+ users to some products, in the form of (userID, productID, rating)
+ pairs. We approximate the ratings matrix as the product of two
--- End diff --
We refer to `pairs` here but `tuple` below. Perhaps this should be
consistent ("tuple" since it's not a pair in fact)
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