Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/10085#discussion_r50160361
--- Diff: python/pyspark/ml/feature.py ---
@@ -992,6 +993,88 @@ def getDegree(self):
@inherit_doc
+class QuantileDiscretizer(JavaEstimator, HasInputCol, HasOutputCol):
+ """
+ .. note:: Experimental
+
+ `QuantileDiscretizer` takes a column with continuous features and
outputs a column with binned
+ categorical features. The bin ranges are chosen by taking a sample of
the data and dividing it
+ into roughly equal parts. The lower and upper bin bounds will be
-Infinity and +Infinity,
+ covering all real values. This attempts to find numBuckets partitions
based on a sample of data,
+ but it may find fewer depending on the data sample values.
+
+ >>> df = sqlContext.createDataFrame([(0.1,), (0.4,), (1.2,), (1.5,)],
["values"])
+ >>> qds = QuantileDiscretizer(numBuckets=2,
+ ... inputCol="values", outputCol="buckets")
+ >>> bucketizer = qds.fit(df)
+ >>> splits = bucketizer.getSplits()
+ >>> splits[0]
+ -inf
+ >>> int(splits[1]*10)
--- End diff --
Its a float, so to make the test not flaky and still human readable for
doctests I truncated the split.
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