Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/9581#issuecomment-161078964
**[Test build #46975 has
finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/46975/consoleFull)**
for PR 9581 at commit
[`ba6ac0a`](https://github.com/apache/spark/commit/ba6ac0affedf493a930e74be4d615b9906342b24).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds the following public classes _(experimental)_:\n * `
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.\", str)`\n * `
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.\", str)`\n * ` thresholds =
Param(Params._dummy(), \"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' thresho
ld.\", None)`\n * ` 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.\", None)`\n
* ` * For example, we build an encoder for `case class Data(a: Int, b:
String)` and the real type`\n * `case class UpCast(child: Expression,
dataType: DataType, walkedTypePath: Seq[String])`\n * ` case class
SubExprEliminationState(isNull: String, value: String)`\n * `case class
InitializeJavaBean(beanInstance: Expression, setters: Map[String,
Expression])`\n
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