Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/6019#issuecomment-101579211
[Test build #32594 has
finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/32594/consoleFull)
for PR 6019 at commit
[`2569168`](https://github.com/apache/spark/commit/2569168e0a7bda1cd78c7f5956430480032b341c).
* This patch **passes all tests**.
* This patch merges cleanly.
* This patch adds the following public classes _(experimental)_:
* `class Pipeline(override val uid: String) extends
Estimator[PipelineModel] `
* `final class DecisionTreeClassifier(override val uid: String)`
* `final class GBTClassifier(override val uid: String)`
* `class LogisticRegression(override val uid: String)`
* `final class OneVsRest(override val uid: String)`
* `final class RandomForestClassifier(override val uid: String)`
* `class BinaryClassificationEvaluator(override val uid: String)`
* `final class Binarizer(override val uid: String)`
* `final class Bucketizer(override val uid: String)`
* `class ElementwiseProduct(override val uid: String)`
* `class HashingTF(override val uid: String) extends
UnaryTransformer[Iterable[_], Vector, HashingTF] `
* `final class IDF(override val uid: String) extends Estimator[IDFModel]
with IDFBase `
* `class Normalizer(override val uid: String) extends
UnaryTransformer[Vector, Vector, Normalizer] `
* `class OneHotEncoder(override val uid: String)`
* `class PolynomialExpansion(override val uid: String)`
* `class StandardScaler(override val uid: String) extends
Estimator[StandardScalerModel]`
* `class StringIndexer(override val uid: String) extends
Estimator[StringIndexerModel]`
* `class Tokenizer(override val uid: String) extends
UnaryTransformer[String, Seq[String], Tokenizer] `
* `class RegexTokenizer(override val uid: String)`
* `class VectorAssembler(override val uid: String)`
* `class VectorIndexer(override val uid: String) extends
Estimator[VectorIndexerModel]`
* `final class Word2Vec(override val uid: String) extends
Estimator[Word2VecModel] with Word2VecBase `
* `class Param[T](val parent: String, val name: String, val doc: String,
val isValid: T => Boolean)`
* `class DoubleParam(parent: String, name: String, doc: String, isValid:
Double => Boolean)`
* `class IntParam(parent: String, name: String, doc: String, isValid: Int
=> Boolean)`
* `class FloatParam(parent: String, name: String, doc: String, isValid:
Float => Boolean)`
* `class LongParam(parent: String, name: String, doc: String, isValid:
Long => Boolean)`
* `class BooleanParam(parent: String, name: String, doc: String) // No
need for isValid`
* `class ALS(override val uid: String) extends Estimator[ALSModel] with
ALSParams `
* `final class DecisionTreeRegressor(override val uid: String)`
* `final class GBTRegressor(override val uid: String)`
* `class LinearRegression(override val uid: String)`
* `final class RandomForestRegressor(override val uid: String)`
* `class CrossValidator(override val uid: String) extends
Estimator[CrossValidatorModel]`
* `trait Identifiable `
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