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-rw-r--r--python/pyspark/ml/feature.py16
1 files changed, 8 insertions, 8 deletions
diff --git a/python/pyspark/ml/feature.py b/python/pyspark/ml/feature.py
index 71dc636b83..97cbee73a0 100644
--- a/python/pyspark/ml/feature.py
+++ b/python/pyspark/ml/feature.py
@@ -985,17 +985,17 @@ class IndexToString(JavaTransformer, HasInputCol, HasOutputCol):
"""
.. note:: Experimental
- A :py:class:`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.
+ A :py:class:`Transformer` that maps a column of indices back to a new column of
+ corresponding string values.
+ The index-string mapping is either from the ML attributes of the input column,
+ or from user-supplied labels (which take precedence over ML attributes).
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 array of labels to be provided by the user, if not supplied or " +
- "empty, column metadata is read for labels")
+ "Optional array of labels specifying index-string mapping." +
+ " If not provided or if empty, then metadata from inputCol is used instead.")
@keyword_only
def __init__(self, inputCol=None, outputCol=None, labels=None):
@@ -1006,8 +1006,8 @@ class IndexToString(JavaTransformer, HasInputCol, HasOutputCol):
self._java_obj = self._new_java_obj("org.apache.spark.ml.feature.IndexToString",
self.uid)
self.labels = Param(self, "labels",
- "Optional array of labels to be provided by the user, if not " +
- "supplied or empty, column metadata is read for labels")
+ "Optional array of labels specifying index-string mapping. If not" +
+ " provided or if empty, then metadata from inputCol is used instead.")
kwargs = self.__init__._input_kwargs
self.setParams(**kwargs)