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[SPARK-19852][PYSPARK][ML] Python StringIndexer supports 'keep' to handle invalid data #18453

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[SPARK-19852][PYSPARK][ML] Python StringIndexer supports 'keep' to handle invalid data #18453

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576e530
[SPARK-19852][PYSPARK][ML] Update Python API for StringIndexer setHan…
Mar 10, 2017
8c04830
fix compilation issues
Mar 10, 2017
79dbf81
doctest
Mar 10, 2017
764e099
update doctest
Mar 10, 2017
9809be9
include changes made by SPARK-11569
Mar 17, 2017
6f3bea8
Move doc tests to tests.py.
yanboliang Jun 28, 2017
320fe08
To override param.
yanboliang Jul 1, 2017
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6 changes: 6 additions & 0 deletions python/pyspark/ml/feature.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2132,6 +2132,12 @@ class StringIndexer(JavaEstimator, HasInputCol, HasOutputCol, HasHandleInvalid,
"frequencyDesc, frequencyAsc, alphabetDesc, alphabetAsc.",
typeConverter=TypeConverters.toString)

handleInvalid = Param(Params._dummy(), "handleInvalid", "how to handle invalid data (unseen " +
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@viirya viirya Jul 1, 2017 •
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Hmm, do we need this? Doesn't StringIndexer already extend HasHandleInvalid?

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@viirya viirya Jul 1, 2017

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Oh. I see. HasHandleInvalid's param doc only describes "skip" and "error" options.

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@yanboliang yanboliang Jul 1, 2017

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Yeah, we use updated handleInvalid to override the one in parent.

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@holdenk holdenk Jul 2, 2017

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We do, although since this is currently the only concrete use of handleInvalid -- but other models are slated to start using it in the future.

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@yanboliang yanboliang Jul 2, 2017

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Yep, we will move to this style at other necessary place.

"labels or NULL values). Options are 'skip' (filter out rows with " +
"invalid data), error (throw an error), or 'keep' (put invalid data " +
"in a special additional bucket, at index numLabels).",
typeConverter=TypeConverters.toString)

@keyword_only
def __init__(self, inputCol=None, outputCol=None, handleInvalid="error",
stringOrderType="frequencyDesc"):
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21 changes: 21 additions & 0 deletions python/pyspark/ml/tests.py
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Expand Up @@ -551,6 +551,27 @@ def test_rformula_string_indexer_order_type(self):
for i in range(0, len(expected)):
self.assertTrue(all(observed[i]["features"].toArray() == expected[i]))

def test_string_indexer_handle_invalid(self):
df = self.spark.createDataFrame([
(0, "a"),
(1, "d"),
(2, None)], ["id", "label"])

si1 = StringIndexer(inputCol="label", outputCol="indexed", handleInvalid="keep",
stringOrderType="alphabetAsc")
model1 = si1.fit(df)
td1 = model1.transform(df)
actual1 = td1.select("id", "indexed").collect()
expected1 = [Row(id=0, indexed=0.0), Row(id=1, indexed=1.0), Row(id=2, indexed=2.0)]
self.assertEqual(actual1, expected1)

si2 = si1.setHandleInvalid("skip")
model2 = si2.fit(df)
td2 = model2.transform(df)
actual2 = td2.select("id", "indexed").collect()
expected2 = [Row(id=0, indexed=0.0), Row(id=1, indexed=1.0)]
self.assertEqual(actual2, expected2)


class HasInducedError(Params):

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