Class/Object

org.apache.spark.ml.h2o.features

DatasetSplitter

Related Docs: object DatasetSplitter | package features

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class DatasetSplitter extends OneTimeTransformer with DatasetSplitterParams with DefaultParamsWritable

Split the dataset and store the splits with the specified keys into DKV It determines the frame which is passed on the output in the following order: 1) If the train key is specified using setTrainKey method and the key is also specified in the list of keys, then frame with this key is passed on the output 2) Otherwise, if the default key - "train.hex" is specified in the list of keys, then frame with this key is passed on the output 3) Otherwise the first frame specified in the list of keys is passed on the output

Linear Supertypes
DefaultParamsWritable, MLWritable, DatasetSplitterParams, OneTimeTransformer, Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. DatasetSplitter
  2. DefaultParamsWritable
  3. MLWritable
  4. DatasetSplitterParams
  5. OneTimeTransformer
  6. Transformer
  7. PipelineStage
  8. Logging
  9. Params
  10. Serializable
  11. Serializable
  12. Identifiable
  13. AnyRef
  14. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new DatasetSplitter()(implicit h2oContext: H2OContext, sqlContext: SQLContext)

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  2. new DatasetSplitter(uid: String)(implicit h2oContext: H2OContext, sqlContext: SQLContext)

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Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

  3. final def $[T](param: Param[T]): T

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    Attributes
    protected
    Definition Classes
    Params

  4. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  6. final def clear(param: Param[_]): DatasetSplitter.this.type

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    Definition Classes
    Params

  7. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  8. def copy(extra: ParamMap): Transformer

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    Definition Classes
    DatasetSplitter → Transformer → PipelineStage → Params

  9. def copyValues[T <: Params](to: T, extra: ParamMap): T

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    Attributes
    protected
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    Params

  10. final def defaultCopy[T <: Params](extra: ParamMap): T

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    Attributes
    protected
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    Params

  11. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef

  12. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  13. def explainParam(param: Param[_]): String

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    Definition Classes
    Params

  14. def explainParams(): String

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    Definition Classes
    Params

  15. final def extractParamMap(): ParamMap

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    Definition Classes
    Params

  16. final def extractParamMap(extra: ParamMap): ParamMap

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    Definition Classes
    Params

  17. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  18. final def get[T](param: Param[T]): Option[T]

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    Definition Classes
    Params

  19. final def getClass(): Class[_]

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    Definition Classes
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  20. final def getDefault[T](param: Param[T]): Option[T]

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    Definition Classes
    Params

  21. def getKeys: Array[String]

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    Definition Classes
    DatasetSplitterParams

  22. final def getOrDefault[T](param: Param[T]): T

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    Definition Classes
    Params

  23. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params

  24. def getRatios: Array[Double]

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    Definition Classes
    DatasetSplitterParams

  25. def getTrainKey: String

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    Definition Classes
    DatasetSplitterParams

  26. implicit val h2oContext: H2OContext

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  27. final def hasDefault[T](param: Param[T]): Boolean

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    Definition Classes
    Params

  28. def hasParam(paramName: String): Boolean

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    Definition Classes
    Params

  29. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  30. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
    Definition Classes
    Logging

  31. final def isDefined(param: Param[_]): Boolean

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  32. final def isInstanceOf[T0]: Boolean

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    Any

  33. final def isSet(param: Param[_]): Boolean

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    Params

  34. def isTraceEnabled(): Boolean

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    Attributes
    protected
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    Logging

  35. final val keys: StringArrayParam

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    By default it is set to Array("train.hex")

    By default it is set to Array("train.hex")

    Definition Classes
    DatasetSplitterParams

  36. def log: Logger

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    Attributes
    protected
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    Logging

  37. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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    Logging

  38. def logDebug(msg: ⇒ String): Unit

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    Logging

  39. def logError(msg: ⇒ String, throwable: Throwable): Unit

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    Logging

  40. def logError(msg: ⇒ String): Unit

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    Logging

  41. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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    Logging

  42. def logInfo(msg: ⇒ String): Unit

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    Logging

  43. def logName: String

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    protected
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    Logging

  44. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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    protected
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    Logging

  45. def logTrace(msg: ⇒ String): Unit

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    Attributes
    protected
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    Logging

  46. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
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    Logging

  47. def logWarning(msg: ⇒ String): Unit

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    Attributes
    protected
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    Logging

  48. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef

  49. final def notify(): Unit

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    Definition Classes
    AnyRef

  50. final def notifyAll(): Unit

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    AnyRef

  51. lazy val params: Array[Param[_]]

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    Definition Classes
    Params

  52. final val ratios: DoubleArrayParam

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    By default it is set to Array(1.0) which does not split the dataset at all

    By default it is set to Array(1.0) which does not split the dataset at all

    Definition Classes
    DatasetSplitterParams

  53. def save(path: String): Unit

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    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )

  54. final def set(paramPair: ParamPair[_]): DatasetSplitter.this.type

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  55. final def set(param: String, value: Any): DatasetSplitter.this.type

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  56. final def set[T](param: Param[T], value: T): DatasetSplitter.this.type

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  57. final def setDefault(paramPairs: ParamPair[_]*): DatasetSplitter.this.type

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  58. final def setDefault[T](param: Param[T], value: T): DatasetSplitter.this.type

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    Params

  59. def setKeys(value: Array[String]): DatasetSplitter

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  60. def setRatios(value: Array[Double]): DatasetSplitter

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  61. def setTrainKey(value: String): DatasetSplitter

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  62. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef

  63. def toString(): String

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    Identifiable → AnyRef → Any

  64. final val trainKey: Param[String]

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    By default it is set to "train.hex"

    By default it is set to "train.hex"

    Definition Classes
    DatasetSplitterParams

  65. def transform(dataset: Dataset[_]): DataFrame

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    Definition Classes
    DatasetSplitter → Transformer

  66. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )

  67. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()

  68. def transformSchema(schema: StructType): StructType

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    Definition Classes
    DatasetSplitter → PipelineStage
    Annotations
    @DeveloperApi()

  69. def transformSchema(schema: StructType, logging: Boolean): StructType

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    Attributes
    protected
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    PipelineStage
    Annotations
    @DeveloperApi()

  70. val uid: String

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    Definition Classes
    DatasetSplitter → Identifiable

  71. final def wait(): Unit

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    @throws( ... )

  72. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )

  73. final def wait(arg0: Long): Unit

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    @throws( ... )

  74. def write: MLWriter

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    Definition Classes
    DefaultParamsWritable → MLWritable

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from DatasetSplitterParams

Inherited from OneTimeTransformer

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

getParam

setParam

setParam When specified trainKey is not in the list of keys, the splitter passes the first split as train dataset

Ungrouped