Class

com.salesforce.op.stages.base.binary

BinaryEstimator

Related Doc: package binary

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abstract class BinaryEstimator[I1 <: FeatureType, I2 <: FeatureType, O <: FeatureType] extends Estimator[BinaryModel[I1, I2, O]] with OpPipelineStage2[I1, I2, O]

Takes a two input features and performs a fit operation in order to define a transformation for those (or similar) features. This abstract class should be extended when settable parameters are needed within the fit function

I1

first input feature type

I2

second input feature type

O

output feature type

Linear Supertypes
OpPipelineStage2[I1, I2, O], HasIn2, HasIn1, OpPipelineStage[O], OpPipelineStageBase, MLWritable, OpPipelineStageParams, InputParams, Estimator[BinaryModel[I1, I2, O]], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Known Subclasses
Ordering
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  2. By Inheritance
Inherited
  1. BinaryEstimator
  2. OpPipelineStage2
  3. HasIn2
  4. HasIn1
  5. OpPipelineStage
  6. OpPipelineStageBase
  7. MLWritable
  8. OpPipelineStageParams
  9. InputParams
  10. Estimator
  11. PipelineStage
  12. Logging
  13. Params
  14. Serializable
  15. Serializable
  16. Identifiable
  17. AnyRef
  18. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new BinaryEstimator(operationName: String, uid: String)(implicit tti1: scala.reflect.api.JavaUniverse.TypeTag[I1], tti2: scala.reflect.api.JavaUniverse.TypeTag[I2], tto: scala.reflect.api.JavaUniverse.TypeTag[O], ttiv1: scala.reflect.api.JavaUniverse.TypeTag[I1.Value], ttiv2: scala.reflect.api.JavaUniverse.TypeTag[I2.Value], ttov: scala.reflect.api.JavaUniverse.TypeTag[O.Value])

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    operationName

    unique name of the operation this stage performs

    uid

    uid for instance

    tti1

    type tag for first input

    tti2

    type tag for second input

    tto

    type tag for output

    ttiv1

    type tag for first input value

    ttiv2

    type tag for second input value

    ttov

    type tag for output value

Type Members

  1. final type InputFeatures = (FeatureLike[I1], FeatureLike[I2])

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    Input Features type

    Input Features type

    Definition Classes
    OpPipelineStage2OpPipelineStageInputParams
  2. final type OutputFeatures = FeatureLike[O]

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    Definition Classes
    OpPipelineStageOpPipelineStageBase

Abstract Value Members

  1. abstract def fitFn(dataset: Dataset[(I1.Value, I2.Value)]): BinaryModel[I1, I2, O]

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    Function that fits the binary model

Concrete 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
    BinaryEstimatorOpPipelineStageBase
  8. final def clear(param: Param[_]): BinaryEstimator.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. val convertI1: FeatureTypeSparkConverter[I1]

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  11. val convertI2: FeatureTypeSparkConverter[I2]

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  12. final def copy(extra: ParamMap): BinaryEstimator.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
  13. def copyValues[T <: Params](to: T, extra: ParamMap): T

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    Attributes
    protected
    Definition Classes
    Params
  14. final def defaultCopy[T <: Params](extra: ParamMap): T

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    Attributes
    protected
    Definition Classes
    Params
  15. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  16. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  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 fit(dataset: Dataset[_]): BinaryModel[I1, I2, O]

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    Spark operation on dataset to produce RDD for constructor fit function and then turn output function into a Model

    Spark operation on dataset to produce RDD for constructor fit function and then turn output function into a Model

    dataset

    input data for this stage

    returns

    a fitted model that will perform the transformation specified by the function defined in constructor fit

    Definition Classes
    BinaryEstimator → Estimator
  23. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[BinaryModel[I1, I2, O]]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  24. def fit(dataset: Dataset[_], paramMap: ParamMap): BinaryModel[I1, I2, O]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  25. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): BinaryModel[I1, I2, O]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  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
    AnyRef → Any
  28. final def getDefault[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  29. 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

  30. 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

  31. final def getInputSchema(): StructType

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

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

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    Definition Classes
    Params
  34. def getOutput(): FeatureLike[O]

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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
    OpPipelineStage2OpPipelineStageBase
  35. 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
  36. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  37. 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
  38. final def getTransientFeatures(): Array[TransientFeature]

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    Gets the input Features

    Gets the input Features

    returns

    input features

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

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

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    Definition Classes
    Params
  41. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  42. implicit val i1Encoder: Encoder[I1.Value]

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  43. implicit val i2Encoder: Encoder[I2.Value]

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  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. def log: Logger

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

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  60. def logName: String

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  65. final def ne(arg0: AnyRef): Boolean

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

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

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    Definition Classes
    AnyRef
  68. def onGetMetadata(): Unit

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    Function to be called on getMetadata

    Function to be called on getMetadata

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

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    Function to be called on setInput

    Function to be called on setInput

    Attributes
    protected
    Definition Classes
    OpPipelineStageBase
  70. val operationName: String

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    unique name of the operation this stage performs

    unique name of the operation this stage performs

    Definition Classes
    BinaryEstimatorOpPipelineStageBase
  71. 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
  72. def outputFeatureUid: String

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    Attributes
    protected[com.salesforce.op]
    Definition Classes
    OpPipelineStage2OpPipelineStage
  73. 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
  74. lazy val params: Array[Param[_]]

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    Definition Classes
    Params
  75. def save(path: String): Unit

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Params
  81. final def setInput(features: InputFeatures): BinaryEstimator.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
  82. final def setInputFeatures[S <: OPFeature](features: Array[S]): BinaryEstimator.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
  83. final def setMetadata(m: Metadata): BinaryEstimator.this.type

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    Definition Classes
    OpPipelineStageParams
  84. def setOutputFeatureName(name: String): BinaryEstimator.this.type

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    Definition Classes
    OpPipelineStage
  85. 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
  86. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  87. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any
  88. 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
  89. def transformSchema(schema: StructType, logging: Boolean): StructType

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  90. implicit val tti1: scala.reflect.api.JavaUniverse.TypeTag[I1]

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    type tag for first input

  91. implicit val tti2: scala.reflect.api.JavaUniverse.TypeTag[I2]

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    type tag for second input

  92. implicit val ttiv1: scala.reflect.api.JavaUniverse.TypeTag[I1.Value]

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    type tag for first input value

  93. implicit val ttiv2: scala.reflect.api.JavaUniverse.TypeTag[I2.Value]

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    type tag for second input value

  94. implicit val tto: scala.reflect.api.JavaUniverse.TypeTag[O]

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    type tag for output

    type tag for output

    Definition Classes
    BinaryEstimatorOpPipelineStage2
  95. implicit val ttov: scala.reflect.api.JavaUniverse.TypeTag[O.Value]

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    type tag for output value

    type tag for output value

    Definition Classes
    BinaryEstimatorOpPipelineStage2
  96. implicit val tupleEncoder: Encoder[(I1.Value, I2.Value)]

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  97. val uid: String

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    uid for instance

    uid for instance

    Definition Classes
    BinaryEstimator → Identifiable
  98. final def wait(): Unit

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

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

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

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    Definition Classes
    OpPipelineStageBase → MLWritable

Inherited from OpPipelineStage2[I1, I2, O]

Inherited from HasIn2

Inherited from HasIn1

Inherited from OpPipelineStage[O]

Inherited from OpPipelineStageBase

Inherited from MLWritable

Inherited from OpPipelineStageParams

Inherited from InputParams

Inherited from Estimator[BinaryModel[I1, I2, O]]

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