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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