Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/8720#issuecomment-139663440
[Test build #42345 has
finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/42345/console)
for PR 8720 at commit
[`2639ffd`](https://github.com/apache/spark/commit/2639ffd092abb9816e70462f62f7346b6fd33832).
* This patch **fails Spark unit tests**.
* This patch merges cleanly.
* This patch adds the following public classes _(experimental)_:
* `class ShuffleDependency[K: ClassTag, V: ClassTag, C: ClassTag](`
* `class CoGroupedRDD[K: ClassTag](`
* `class ShuffledRDD[K: ClassTag, V: ClassTag, C: ClassTag](`
* `class MultilayerPerceptronClassifier(JavaEstimator, HasFeaturesCol,
HasLabelCol, HasPredictionCol,`
* `class MultilayerPerceptronClassificationModel(JavaModel):`
* `class StringIndexer(JavaEstimator, HasInputCol, HasOutputCol,
HasHandleInvalid):`
* ` ("thresholds", "Thresholds in multi-class classification to
adjust the probability of " +`
* `class HasHandleInvalid(Params):`
* `class HasElasticNetParam(Params):`
* `class HasFitIntercept(Params):`
* `class HasStandardization(Params):`
* `class HasThresholds(Params):`
* ` 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' threshold.")`
* ` 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.")`
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