Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/12938#discussion_r65778263
--- Diff: python/pyspark/ml/classification.py ---
@@ -183,7 +191,7 @@ def getThresholds(self):
If :py:attr:`thresholds` is set, return its value.
Otherwise, if :py:attr:`threshold` is set, return the equivalent
thresholds for binary
classification: (1-threshold, threshold).
- If neither are set, throw an error.
--- End diff --
If neither are explicitly set, it does in fact throw an error:
```
In [22]: if not lr.isSet(lr.thresholds) and lr.isSet(lr.threshold):
....: t = lr.getOrDefault(lr.threshold)
....: [1.0-t, t]
....: else:
....: lr.getOrDefault(lr.thresholds)
....:
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-22-869f82439552> in <module>()
3 [1.0-t, t]
4 else:
----> 5 lr.getOrDefault(lr.thresholds)
6
/Users/nick/workspace/scala/mlnick-spark/python/pyspark/ml/param/__init__.pyc
in getOrDefault(self, param)
348 return self._paramMap[param]
349 else:
--> 350 return self._defaultParamMap[param]
351
352 @since("1.4.0")
KeyError: Param(parent=u'LogisticRegression_4b97b6978cdc41d90ee3',
name='thresholds', doc="Thresholds in multi-class classification to adjust the
probability of predicting each class. Array must have length equal to the
number of classes, with values >= 0. The class with largest value p/t is
predicted, where p is the original probability of that class and t is the
class' threshold.")
```
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