Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/8214#issuecomment-142203284
[Test build #42821 has
finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/42821/console)
for PR 8214 at commit
[`269bfc8`](https://github.com/apache/spark/commit/269bfc8c23b062491c43eac904c62f0f7b67d008).
* This patch **passes all tests**.
* This patch merges cleanly.
* This patch adds the following public classes _(experimental)_:
* ` ("probabilityCol", "Column name for predicted class
conditional probabilities " +`
* ` probabilityCol = Param(Params._dummy(), "probabilityCol", "Column
name for predicted class conditional probabilities Note: Not all models output
well-calibrated probability estimates! These probabilities should be treated as
confidences, not precise probabilities.")`
* ` self.probabilityCol = Param(self, "probabilityCol", "Column
name for predicted class conditional probabilities Note: Not all models output
well-calibrated probability estimates! These probabilities should be treated as
confidences, not precise probabilities")`
* ` self.thresholds = Param(self, "thresholds", "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")`
* `class HasWeightCol(Params):`
* `class IsotonicRegression(JavaEstimator, HasFeaturesCol, HasLabelCol,
HasPredictionCol,`
* `class IsotonicRegressionModel(JavaModel):`
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