Github user jkbradley commented on a diff in the pull request: https://github.com/apache/spark/pull/15428#discussion_r84731699 --- Diff: python/pyspark/ml/feature.py --- @@ -1157,9 +1157,11 @@ class QuantileDiscretizer(JavaEstimator, HasInputCol, HasOutputCol, JavaMLReadab categorical features. The number of bins can be set using the :py:attr:`numBuckets` parameter. It is possible that the number of buckets used will be less than this value, for example, if there are too few distinct values of the input to create enough distinct quantiles. Note also - that NaN values are handled specially and placed into their own bucket. For example, if 4 - buckets are used, then non-NaN data will be put into buckets(0-3), but NaNs will be counted in - a special bucket(4). + that QuantileDiscretizer will raise an error when it finds NaN value in the dataset, but user --- End diff -- This isn't available in Python yet, so can you please revert this change to feature.py?
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