Major Description
In my dev setups, ml.recommendation:ALS test consistently converges to value lower than expected and fails with:
File "/path/to/spark/python/pyspark/ml/recommendation.py", line 322, in __main__.ALS Failed example: predictions[0] Expected: Row(user=0, item=2, newPrediction=0.69291...) Got: Row(user=0, item=2, newPrediction=0.6929099559783936)
In can correct for that, but it creates some noise, so if anyone else experiences this, we could drop a digit from the results
diff --git a/python/pyspark/ml/recommendation.py b/python/pyspark/ml/recommendation.py index f0628fb922..b8e2a6097d 100644 --- a/python/pyspark/ml/recommendation.py +++ b/python/pyspark/ml/recommendation.py @@ -320,7 +320,7 @@ class ALS(JavaEstimator, _ALSParams, JavaMLWritable, JavaMLReadable): >>> test = spark.createDataFrame([(0, 2), (1, 0), (2, 0)], ["user", "item"]) >>> predictions = sorted(model.transform(test).collect(), key=lambda r: r[0]) >>> predictions[0] - Row(user=0, item=2, newPrediction=0.69291...) + Row(user=0, item=2, newPrediction=0.6929...) >>> predictions[1] Row(user=1, item=0, newPrediction=3.47356...) >>> predictions[2]
