Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/7432#discussion_r35788742
--- Diff: python/pyspark/ml/classification.py ---
@@ -299,9 +299,9 @@ class RandomForestClassifier(JavaEstimator,
HasFeaturesCol, HasLabelCol, HasPred
>>> stringIndexer = StringIndexer(inputCol="label",
outputCol="indexed")
>>> si_model = stringIndexer.fit(df)
>>> td = si_model.transform(df)
- >>> rf = RandomForestClassifier(numTrees=2, maxDepth=2,
labelCol="indexed", seed=42)
+ >>> rf = RandomForestClassifier(numTrees=3, maxDepth=2,
labelCol="indexed", seed=42)
--- End diff --
As mentioned in the git commit, it's actually tied at 2 tries so the change
in how we selected it changed the prediction (since when its tied one would
grab the first and the other the last), so I switched it to three trees so it
wouldn't be tied and the test would be testing what we were looking for. I'll
make a JIRA to update the Python API after my morning standup :)
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