viirya commented on a change in pull request #25812: [SPARK-22796][PYTHON][ML]
Add multiple columns support to PySpark QuantileDiscretizer
URL: https://github.com/apache/spark/pull/25812#discussion_r325393980
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File path: python/pyspark/ml/feature.py
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@@ -1959,13 +1959,18 @@ def getDegree(self):
@inherit_doc
-class QuantileDiscretizer(JavaEstimator, HasInputCol, HasOutputCol,
HasHandleInvalid,
- JavaMLReadable, JavaMLWritable):
+class QuantileDiscretizer(JavaEstimator, HasInputCol, HasOutputCol,
HasInputCols, HasOutputCols,
+ HasHandleInvalid, JavaMLReadable, JavaMLWritable):
"""
`QuantileDiscretizer` takes a column with continuous features and outputs
a column with binned
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.
+ Since 3.0.0, :py:class:`QuantileDiscretizer` can map multiple columns at
once by setting the
Review comment:
above there is a ``` `QuantileDiscretizer` ```, add :py:class: to make it
consistent?
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