Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/7976#discussion_r37726435
--- Diff: python/pyspark/ml/feature.py ---
@@ -817,6 +822,64 @@ class StringIndexerModel(JavaModel):
"""
Model fitted by StringIndexer.
"""
+ @property
+ def labels(self):
+ return self._java_obj.labels
+
+
+@inherit_doc
+class IndexToString(JavaTransformer, HasInputCol, HasOutputCol):
+ """
+ .. note:: Experimental
+ A [[Transformer]] that maps a column of string indices back to a new
column of corresponding
+ string values using either the ML attributes of the input column, or
if provided using the
+ labels supplied by the user.
+ All original columns are kept during transformation.
+ See L{StringIndexer} for converting strings into indices
+ """
+
+ # a placeholder to make the labels show up in generated doc
+ labels = Param(Params._dummy(), "labels",
+ "Optional labels to be provided by the user, if not
supplied column " +
+ "metadata is read for labels. The default value is an
empty array, " +
+ "but the empty array is ignored and column metadata
used instead.")
+
+ @keyword_only
+ def __init__(self, inputCol=None, outputCol=None, labels=[]):
--- End diff --
My concern is the underlying Scala code uses an empty array as the default.
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