Class

com.salesforce.op.stages.impl.selector

SelectedModel

Related Doc: package selector

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final class SelectedModel extends Model[SelectedModel] with SparkWrapperParams[Model[_]] with OpTransformer2[RealNN, OPVector, Prediction] with HasTestEval

Returned wrapped best model from model selector estimator

Linear Supertypes
HasTestEval, HasEval, OpTransformer2[RealNN, OPVector, Prediction], OpTransformer, OpPipelineStage2[RealNN, OPVector, Prediction], HasOut[Prediction], HasIn2, HasIn1, OpPipelineStage[Prediction], OpPipelineStageBase, MLWritable, OpPipelineStageParams, InputParams, SparkWrapperParams[Model[_]], Model[SelectedModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. SelectedModel
  2. HasTestEval
  3. HasEval
  4. OpTransformer2
  5. OpTransformer
  6. OpPipelineStage2
  7. HasOut
  8. HasIn2
  9. HasIn1
  10. OpPipelineStage
  11. OpPipelineStageBase
  12. MLWritable
  13. OpPipelineStageParams
  14. InputParams
  15. SparkWrapperParams
  16. Model
  17. Transformer
  18. PipelineStage
  19. Logging
  20. Params
  21. Serializable
  22. Serializable
  23. Identifiable
  24. AnyRef
  25. Any
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Visibility
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Type Members

  1. final type InputFeatures = (FeatureLike[RealNN], FeatureLike[OPVector])

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    Input Features type

    Input Features type

    Definition Classes
    OpPipelineStage2OpPipelineStageInputParams
  2. type KeyValue = (String) ⇒ Any

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    Feature name (key) -> value lookup, e.g Row, Map etc.

    Feature name (key) -> value lookup, e.g Row, Map etc.

    Definition Classes
    OpTransformer
  3. final type OutputFeatures = FeatureLike[Prediction]

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    Definition Classes
    OpPipelineStageOpPipelineStageBase

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 checkInputLength(features: Array[_]): Boolean

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    Checks the input length

    Checks the input length

    features

    input features

    returns

    true is input size as expected, false otherwise

    Definition Classes
    OpPipelineStage2InputParams
  7. final def checkSerializable: Try[Unit]

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    Check if the stage is serializable

    Check if the stage is serializable

    returns

    Failure if not serializable

    Definition Classes
    OpTransformer2OpPipelineStageBase
  8. final def clear(param: Param[_]): SelectedModel.this.type

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    Definition Classes
    Params
  9. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  10. final def copy(extra: ParamMap): SelectedModel.this.type

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    This method is used to make a copy of the instance with new parameters in several methods in spark internals Default will find the constructor and make a copy for any class (AS LONG AS ALL CONSTRUCTOR PARAMS ARE VALS, this is why type tags are written as implicit vals in base classes).

    This method is used to make a copy of the instance with new parameters in several methods in spark internals Default will find the constructor and make a copy for any class (AS LONG AS ALL CONSTRUCTOR PARAMS ARE VALS, this is why type tags are written as implicit vals in base classes).

    Note: that the convention in spark is to have the uid be a constructor argument, so that copies will share a uid with the original (developers should follow this convention).

    extra

    new parameters want to add to instance

    returns

    a new instance with the same uid

    Definition Classes
    OpPipelineStageBase → Params
  11. def copyValues[T <: Params](to: T, extra: ParamMap): T

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    Attributes
    protected
    Definition Classes
    Params
  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 evaluate(data: Dataset[_]): EvaluationMetrics

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    Function that evaluates the selected model on the test set

    Function that evaluates the selected model on the test set

    data

    data transformed by best model

    returns

    EvaluationMetrics

    Attributes
    protected
    Definition Classes
    HasEval
  16. def evaluators: Seq[OpEvaluatorBase[_ <: EvaluationMetrics]]

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    Definition Classes
    SelectedModel → HasEval
  17. def explainParam(param: Param[_]): String

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    Definition Classes
    Params
  18. def explainParams(): String

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    Definition Classes
    Params
  19. final def extractParamMap(): ParamMap

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    Definition Classes
    Params
  20. final def extractParamMap(extra: ParamMap): ParamMap

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    Definition Classes
    Params
  21. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  22. def fullPredictionColName: Option[String]

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    Attributes
    protected[com.salesforce.op]
    Definition Classes
    HasEval
  23. final def get[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  24. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any
  25. final def getDefault[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  26. def getInputColParamNames(): Array[String]

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    Gets names of parameters that control input columns for Spark stage

    Gets names of parameters that control input columns for Spark stage

    Definition Classes
    SparkWrapperParams
  27. final def getInputFeature[T <: FeatureType](i: Int): Option[FeatureLike[T]]

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    Gets an input feature Note: this method IS NOT safe to use outside the driver, please use getTransientFeature method instead

    Gets an input feature Note: this method IS NOT safe to use outside the driver, please use getTransientFeature method instead

    returns

    array of features

    Definition Classes
    InputParams
    Exceptions thrown

    NoSuchElementException if the features are not set

    RuntimeException in case one of the features is null

  28. final def getInputFeatures(): Array[OPFeature]

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    Gets the input features Note: this method IS NOT safe to use outside the driver, please use getTransientFeatures method instead

    Gets the input features Note: this method IS NOT safe to use outside the driver, please use getTransientFeatures method instead

    returns

    array of features

    Definition Classes
    InputParams
    Exceptions thrown

    NoSuchElementException if the features are not set

    RuntimeException in case one of the features is null

  29. final def getInputSchema(): StructType

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    Definition Classes
    OpPipelineStageParams
  30. final def getMetadata(): Metadata

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    Definition Classes
    OpPipelineStageParams
  31. final def getOrDefault[T](param: Param[T]): T

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    Definition Classes
    Params
  32. def getOutput(): FeatureLike[Prediction]

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    Output features that will be created by this stage

    Output features that will be created by this stage

    returns

    feature of type OutputFeatures

    Definition Classes
    HasOut → OpPipelineStageBase
  33. def getOutputColParamNames(): Array[String]

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    Gets names of parameters that control output columns for Spark stage

    Gets names of parameters that control output columns for Spark stage

    Definition Classes
    SparkWrapperParams
  34. final def getOutputFeatureName: String

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    Name of output feature (i.e.

    Name of output feature (i.e. column created by this stage)

    Definition Classes
    OpPipelineStage
  35. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  36. def getSparkMlStage(): Option[Model[_]]

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    Method to access the spark stage being wrapped

    Method to access the spark stage being wrapped

    returns

    Option of spark ml stage

    Definition Classes
    SparkWrapperParams
  37. def getStageSavePath(): Option[String]

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    Gets a save path for wrapped spark stage

    Gets a save path for wrapped spark stage

    Definition Classes
    SparkWrapperParams
  38. final def getTransientFeature(i: Int): Option[TransientFeature]

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    Gets an input feature at index i

    Gets an input feature at index i

    i

    input index

    returns

    maybe an input feature

    Definition Classes
    InputParams
  39. final def getTransientFeatures(): Array[TransientFeature]

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    Gets the input Features

    Gets the input Features

    returns

    input features

    Definition Classes
    InputParams
  40. final def hasDefault[T](param: Param[T]): Boolean

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    Definition Classes
    Params
  41. def hasParam(paramName: String): Boolean

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    Definition Classes
    Params
  42. def hasParent: Boolean

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    Definition Classes
    Model
  43. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  44. final def in1: TransientFeature

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    Attributes
    protected
    Definition Classes
    HasIn1
  45. final def in2: TransientFeature

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    Attributes
    protected
    Definition Classes
    HasIn2
  46. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  47. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  48. final def inputAsArray(in: InputFeatures): Array[OPFeature]

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    Function to convert InputFeatures to an Array of FeatureLike

    Function to convert InputFeatures to an Array of FeatureLike

    returns

    an Array of FeatureLike

    Definition Classes
    OpPipelineStage2InputParams
  49. final def isDefined(param: Param[_]): Boolean

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    Definition Classes
    Params
  50. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  51. final def isSet(param: Param[_]): Boolean

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    Definition Classes
    Params
  52. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  53. lazy val labelColName: String

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    Definition Classes
    SelectedModel → HasEval
  54. def log: Logger

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    Attributes
    protected
    Definition Classes
    Logging
  55. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  56. def logDebug(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  57. def logError(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  58. def logError(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  59. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  60. def logInfo(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  61. def logName: String

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    Attributes
    protected
    Definition Classes
    Logging
  62. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  63. def logTrace(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  64. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  65. def logWarning(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  66. val modelStageIn: ModelType

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    the best model from those tried in the estimator

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

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    Definition Classes
    AnyRef
  68. final def notify(): Unit

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    Definition Classes
    AnyRef
  69. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  70. def onGetMetadata(): Unit

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    Function to be called on getMetadata

    Function to be called on getMetadata

    Attributes
    protected
    Definition Classes
    OpPipelineStageParams
  71. def onSetInput(): Unit

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    Function to be called on setInput

    Function to be called on setInput

    Attributes
    protected
    Definition Classes
    InputParams
  72. val operationName: String

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    name of stage

    name of stage

    Definition Classes
    SelectedModelOpPipelineStageBase
  73. final def outputAsArray(out: OutputFeatures): Array[OPFeature]

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    Function to convert OutputFeatures to an Array of FeatureLike

    Function to convert OutputFeatures to an Array of FeatureLike

    returns

    an Array of FeatureLike

    Definition Classes
    OpPipelineStageOpPipelineStageBase
  74. def outputFeatureUid: String

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    Attributes
    protected[com.salesforce.op]
    Definition Classes
    OpPipelineStage2OpPipelineStage
  75. def outputIsResponse: Boolean

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    Should output feature be a response? Yes, if any of the input features are.

    Should output feature be a response? Yes, if any of the input features are.

    returns

    true if the the output feature should be a response

    Definition Classes
    OpPipelineStage
  76. val outputsColNamesMap: Map[String, String]

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    a map of the output names for the estimator

    a map of the output names for the estimator

    Definition Classes
    SelectedModel → HasEval
  77. lazy val params: Array[Param[_]]

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    Definition Classes
    Params
  78. var parent: Estimator[SelectedModel]

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    Definition Classes
    Model
  79. def save(path: String): Unit

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    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  80. final def set(paramPair: ParamPair[_]): SelectedModel.this.type

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    Attributes
    protected
    Definition Classes
    Params
  81. final def set(param: String, value: Any): SelectedModel.this.type

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    Attributes
    protected
    Definition Classes
    Params
  82. final def set[T](param: Param[T], value: T): SelectedModel.this.type

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    Definition Classes
    Params
  83. final def setDefault(paramPairs: ParamPair[_]*): SelectedModel.this.type

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    Attributes
    protected
    Definition Classes
    Params
  84. final def setDefault[T](param: Param[T], value: T): SelectedModel.this.type

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    Attributes
    protected
    Definition Classes
    Params
  85. def setEvaluators(ev: Seq[OpEvaluatorBase[_ <: EvaluationMetrics]]): SelectedModel.this.type

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  86. final def setInput(features: InputFeatures): SelectedModel.this.type

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    Input features that will be used by the stage

    Input features that will be used by the stage

    returns

    feature of type InputFeatures

    Definition Classes
    OpPipelineStageBase
  87. final def setInputFeatures[S <: OPFeature](features: Array[S]): SelectedModel.this.type

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    Sets input features

    Sets input features

    S

    feature like type

    features

    array of input features

    returns

    this stage

    Attributes
    protected
    Definition Classes
    InputParams
  88. final def setMetadata(m: Metadata): SelectedModel.this.type

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    Definition Classes
    OpPipelineStageParams
  89. def setOutputFeatureName(name: String): SelectedModel.this.type

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    Definition Classes
    OpPipelineStage
  90. def setParent(parent: Estimator[SelectedModel]): SelectedModel

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    Definition Classes
    Model
  91. def setSparkMlStage(stage: Option[Model[_]]): SelectedModel.this.type

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    Attributes
    protected
    Definition Classes
    SparkWrapperParams
  92. def setStageSavePath(path: String): SelectedModel.this.type

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    Sets a save path for wrapped spark stage

    Sets a save path for wrapped spark stage

    Definition Classes
    SparkWrapperParams
  93. final val sparkInputColParamNames: StringArrayParam

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    Definition Classes
    SparkWrapperParams
  94. final val sparkMlStage: SparkStageParam[Model[_]]

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    Definition Classes
    SparkWrapperParams
  95. final val sparkOutputColParamNames: StringArrayParam

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    Definition Classes
    SparkWrapperParams
  96. final def stageName: String

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    Stage unique name consisting of the stage operation name and uid

    Stage unique name consisting of the stage operation name and uid

    returns

    stage name

    Definition Classes
    OpPipelineStageBase
  97. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  98. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any
  99. def transform(dataset: Dataset[_]): DataFrame

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    Spark operation on dataset to produce new output feature column using defined function

    Spark operation on dataset to produce new output feature column using defined function

    dataset

    input data for this stage

    returns

    a new dataset containing a column for the transformed feature

    Definition Classes
    OpTransformer2 → Transformer
  100. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  101. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  102. def transformFn: (RealNN, OPVector) ⇒ Prediction

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    Function used to convert input to output

    Function used to convert input to output

    Definition Classes
    SelectedModelOpTransformer2
  103. lazy val transformKeyValue: (KeyValue) ⇒ Any

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    Creates a transform function to transform any key/value to a value

    Creates a transform function to transform any key/value to a value

    returns

    a transform function to transform any key/value to a value

    Definition Classes
    OpTransformer2 → OpTransformer
  104. def transformMap: (Map[String, Any]) ⇒ Any

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    Creates a transform function to transform Map to a value

    Creates a transform function to transform Map to a value

    returns

    a transform function to transform Map to a value

    Definition Classes
    OpTransformer
  105. def transformRow: (Row) ⇒ Any

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    Creates a transform function to transform Row to a value

    Creates a transform function to transform Row to a value

    returns

    a transform function to transform Row to a value

    Definition Classes
    OpTransformer
  106. final def transformSchema(schema: StructType): StructType

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    This function translates the input and output features into spark schema checks and changes that will occur on the underlying data frame

    This function translates the input and output features into spark schema checks and changes that will occur on the underlying data frame

    schema

    schema of the input data frame

    returns

    a new schema with the output features added

    Definition Classes
    OpPipelineStageBase
  107. def transformSchema(schema: StructType, logging: Boolean): StructType

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  108. implicit val tti1: scala.reflect.api.JavaUniverse.TypeTag[RealNN]

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    type tag for RealNN

    type tag for RealNN

    Definition Classes
    SelectedModelOpTransformer2
  109. implicit val tti2: scala.reflect.api.JavaUniverse.TypeTag[OPVector]

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    type tag for OPVector

    type tag for OPVector

    Definition Classes
    SelectedModelOpTransformer2
  110. implicit val tto: scala.reflect.api.JavaUniverse.TypeTag[Prediction]

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    type tag for Prediction

    type tag for Prediction

    Definition Classes
    SelectedModel → HasOut
  111. implicit val ttov: scala.reflect.api.JavaUniverse.TypeTag[Map[String, Double]]

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    type tag for Prediction internal map

    type tag for Prediction internal map

    Definition Classes
    SelectedModel → HasOut
  112. val uid: String

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    uid of the stage

    uid of the stage

    Definition Classes
    SelectedModel → Identifiable
  113. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  114. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  115. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  116. final def write: MLWriter

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    Definition Classes
    OpPipelineStageBase → MLWritable

Inherited from HasTestEval

Inherited from HasEval

Inherited from OpTransformer

Inherited from HasOut[Prediction]

Inherited from HasIn2

Inherited from HasIn1

Inherited from OpPipelineStage[Prediction]

Inherited from OpPipelineStageBase

Inherited from MLWritable

Inherited from OpPipelineStageParams

Inherited from InputParams

Inherited from SparkWrapperParams[Model[_]]

Inherited from Model[SelectedModel]

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

Ungrouped