Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/7903#discussion_r36153134
--- Diff: python/pyspark/ml/classification.py ---
@@ -320,8 +322,13 @@ class RandomForestClassifier(JavaEstimator,
HasFeaturesCol, HasLabelCol, HasPred
>>> allclose(model.treeWeights, [1.0, 1.0, 1.0])
True
>>> test0 = sqlContext.createDataFrame([(Vectors.dense(-1.0),)],
["features"])
- >>> model.transform(test0).head().prediction
+ >>> result = model.transform(test0).head()
+ >>> result.prediction
0.0
+ >>> numpy.argmax(result.probability)
+ 0
+ >>> numpy.argmax(result.rawPrediction)
+ 0
--- End diff --
Here users may want to know the raw prediction and probability prediction
result as the confidence measure, so I think output ```result.probability``` or
```numpy.amax(result.probability)``` is better to demonstrate how to use this
feature.
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