Class

org.apache.spark.ml.odkl.CombinedModel

PerTypeModelLearner

Related Doc: package CombinedModel

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class PerTypeModelLearner[M <: ModelWithSummary[M]] extends ForkedEstimator[M, String, SelectingModel[M]] with HasTypeCol with HasPredictionCol

Collects types, available in the dataset and trains one model per each type.

Linear Supertypes
HasPredictionCol, HasTypeCol, ForkedEstimator[M, String, SelectingModel[M]], ForkedModelParams, SummarizableEstimator[SelectingModel[M]], Estimator[SelectingModel[M]], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. PerTypeModelLearner
  2. HasPredictionCol
  3. HasTypeCol
  4. ForkedEstimator
  5. ForkedModelParams
  6. SummarizableEstimator
  7. Estimator
  8. PipelineStage
  9. Logging
  10. Params
  11. Serializable
  12. Serializable
  13. Identifiable
  14. AnyRef
  15. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new PerTypeModelLearner(nested: SummarizableEstimator[M])

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  2. new PerTypeModelLearner(nested: SummarizableEstimator[M], uid: String)

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    nested

    Nested estimator or fitting.

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[_]): PerTypeModelLearner.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): PerTypeModelLearner[M]

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    Definition Classes
    PerTypeModelLearner → SummarizableEstimator → Estimator → PipelineStage → Params

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

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    Attributes
    protected
    Definition Classes
    Params

  10. def createForkSource(dataset: Dataset[_]): ForkSource[M, String, SelectingModel[M]]

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    Attributes
    protected
    Definition Classes
    ForkedEstimator

  11. def createForks(dataset: Dataset[_]): Seq[(String, DataFrame)]

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    Override this method and create forks to train from the data.

    Override this method and create forks to train from the data.

    Attributes
    protected
    Definition Classes
    PerTypeModelLearner → ForkedEstimator

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

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    Attributes
    protected
    Definition Classes
    Params

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

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    Definition Classes
    AnyRef

  14. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    Params

  16. def explainParams(): String

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    Definition Classes
    Params

  17. final def extractParamMap(): ParamMap

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    Definition Classes
    Params

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

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    Definition Classes
    Params

  19. def failFast(key: String, triedIn: Try[M]): Try[M]

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    Attributes
    protected
    Definition Classes
    ForkedEstimator

  20. def finalize(): Unit

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

  21. def fit(dataset: Dataset[_]): SelectingModel[M]

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    Definition Classes
    ForkedEstimator → Estimator

  22. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[SelectingModel[M]]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )

  23. def fit(dataset: Dataset[_], paramMap: ParamMap): SelectingModel[M]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )

  24. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): SelectingModel[M]

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

  25. def fitFork(estimator: SummarizableEstimator[M], wholeData: Dataset[_], partialData: (String, DataFrame)): (String, Try[M])

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    Definition Classes
    ForkedEstimator

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

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    Definition Classes
    Params

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

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    Definition Classes
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  28. def getCurrentContext: Seq[String]

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    Attributes
    protected
    Definition Classes
    ForkedEstimator

  29. final def getDefault[T](param: Param[T]): Option[T]

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    Definition Classes
    Params

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

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    Definition Classes
    Params

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

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    Definition Classes
    Params

  32. final def getPredictionCol: String

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    Definition Classes
    HasPredictionCol

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

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    Definition Classes
    Params

  34. def hasParam(paramName: String): Boolean

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    Definition Classes
    Params

  35. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  36. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

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    Attributes
    protected
    Definition Classes
    Logging

  37. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Definition Classes
    Params

  39. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    Params

  41. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging

  42. def log: Logger

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

  49. def logName: String

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

  54. def mayBePropagateKey(data: DataFrame, key: Any): DataFrame

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    Attributes
    protected
    Definition Classes
    ForkedModelParams

  55. def mergeModels(sqlContext: SQLContext, models: Seq[(String, Try[M])]): SelectingModel[M]

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    Given models trained for each fork create a combined model.

    Given models trained for each fork create a combined model. This model is the result of the estimator.

    Attributes
    protected
    Definition Classes
    PerTypeModelLearner → ForkedEstimator

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

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    Definition Classes
    AnyRef

  57. val nested: SummarizableEstimator[M]

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    Nested estimator to call for each fork.

    Nested estimator to call for each fork.

    Definition Classes
    ForkedEstimator

  58. final def notify(): Unit

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    Definition Classes
    AnyRef

  59. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  60. final val numThreads: IntParam

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    Definition Classes
    ForkedEstimator

  61. final val overwriteModels: BooleanParam

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    Definition Classes
    ForkedEstimator

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

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    Definition Classes
    Params

  63. final val pathForTempModels: Param[String]

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    Definition Classes
    ForkedEstimator

  64. final val persistingKeyColumns: StringArrayParam

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    Definition Classes
    ForkedEstimator

  65. final val predictionCol: Param[String]

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    Definition Classes
    HasPredictionCol

  66. final val propagatedKeyColumn: Param[String]

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    Definition Classes
    ForkedModelParams

  67. final def set(paramPair: ParamPair[_]): PerTypeModelLearner.this.type

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    Attributes
    protected
    Definition Classes
    Params

  68. final def set(param: String, value: Any): PerTypeModelLearner.this.type

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    Attributes
    protected
    Definition Classes
    Params

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

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    Definition Classes
    Params

  70. final def setDefault(paramPairs: ParamPair[_]*): PerTypeModelLearner.this.type

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    Attributes
    protected
    Definition Classes
    Params

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

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    Attributes
    protected
    Definition Classes
    Params

  72. def setNumThreads(value: Int): PerTypeModelLearner.this.type

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    Definition Classes
    ForkedEstimator

  73. def setOverwriteModels(value: Boolean): PerTypeModelLearner.this.type

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    Definition Classes
    ForkedEstimator

  74. def setPathForTempModels(value: String): PerTypeModelLearner.this.type

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    Definition Classes
    ForkedEstimator

  75. def setPredictionCol(value: String): PerTypeModelLearner.this.type

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  76. def setPropagatedKeyColumn(value: String): PerTypeModelLearner.this.type

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    Definition Classes
    ForkedModelParams

  77. def setTypeColumn(value: String): PerTypeModelLearner.this.type

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    Definition Classes
    HasTypeCol

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

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    Definition Classes
    AnyRef

  79. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any

  80. def transformSchema(schema: StructType): StructType

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    Definition Classes
    ForkedEstimator → PipelineStage
    Annotations
    @DeveloperApi()

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

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()

  82. final val typeColumn: Param[String]

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    Definition Classes
    HasTypeCol

  83. val uid: String

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    Definition Classes
    PerTypeModelLearner → ForkedEstimator → Identifiable

  84. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from HasPredictionCol

Inherited from HasTypeCol

Inherited from ForkedEstimator[M, String, SelectingModel[M]]

Inherited from ForkedModelParams

Inherited from SummarizableEstimator[SelectingModel[M]]

Inherited from Estimator[SelectingModel[M]]

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Ungrouped