Class

com.salesforce.op.stages.impl.feature

OpTextPivotVectorizer

Related Doc: package feature

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class OpTextPivotVectorizer[T <: Text] extends OpOneHotVectorizer[T]

Converts a sequence of Text features into a vector keeping the top K most common occurrences of each feature (ie the final vector has length K * number of inputs). Plus an additional column for "other" values - which will capture values that do not make the cut or values not seen in training, and an additional column for empty values unless null tracking is disabled.

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Inherited
  1. OpTextPivotVectorizer
  2. OpOneHotVectorizer
  3. OneHotFun
  4. MinSupportParam
  5. TrackNullsParam
  6. SaveOthersParams
  7. CleanTextFun
  8. PivotParams
  9. TextParams
  10. VectorizerDefaults
  11. SequenceEstimator
  12. OpPipelineStageN
  13. HasInN
  14. OpPipelineStage
  15. OpPipelineStageBase
  16. MLWritable
  17. OpPipelineStageParams
  18. InputParams
  19. Estimator
  20. PipelineStage
  21. Logging
  22. Params
  23. Serializable
  24. Serializable
  25. Identifiable
  26. AnyRef
  27. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new OpTextPivotVectorizer(operationName: String = "pivotText", uid: String = UID[OpSetVectorizer[_]])(implicit tti: scala.reflect.api.JavaUniverse.TypeTag[T], ttiv: scala.reflect.api.JavaUniverse.TypeTag[Option[String]])

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    operationName

    unique name of the operation this stage performs

    uid

    uid for instance

Type Members

  1. final type InputFeatures = Array[FeatureLike[T]]

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    Input Features type

    Input Features type

    Definition Classes
    OpPipelineStageNOpPipelineStageInputParams
  2. final type OutputFeatures = FeatureLike[OPVector]

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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. implicit def booleanToDouble(v: Boolean): Double

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    Definition Classes
    VectorizerDefaults
  7. 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
    OpPipelineStageNInputParams
  8. 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
    SequenceEstimatorOpPipelineStageBase
  9. final val cleanText: BooleanParam

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    Definition Classes
    TextParams
  10. def cleanTextFn(s: String, shouldClean: Boolean): String

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    Definition Classes
    CleanTextFun
  11. final def clear(param: Param[_]): OpTextPivotVectorizer.this.type

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    Definition Classes
    Params
  12. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  13. def convertToSeqOfMaps(dataset: Dataset[Seq[Option[String]]]): RDD[Seq[Map[String, Int]]]

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    Attributes
    protected
    Definition Classes
    OpTextPivotVectorizerOpOneHotVectorizer
  14. final def copy(extra: ParamMap): OpTextPivotVectorizer.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
  15. def copyValues[T <: Params](to: T, extra: ParamMap): T

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

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

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

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    Definition Classes
    AnyRef → Any
  19. def explainParam(param: Param[_]): String

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    Definition Classes
    Params
  20. def explainParams(): String

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

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

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    Definition Classes
    Params
  23. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  24. def fit(dataset: Dataset[_]): SequenceModel[T, OPVector]

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

    Spark operation on dataset to produce Dataset 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
    SequenceEstimator → Estimator
  25. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[SequenceModel[T, OPVector]]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  26. def fit(dataset: Dataset[_], paramMap: ParamMap): SequenceModel[T, OPVector]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  27. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): SequenceModel[T, OPVector]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  28. def fitFn(dataset: Dataset[Seq[T.Value]]): SequenceModel[T, OPVector]

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    Function that fits the sequence model

    Function that fits the sequence model

    Definition Classes
    OpOneHotVectorizerSequenceEstimator
  29. final def get[T](param: Param[T]): Option[T]

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

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

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    Definition Classes
    Params
  32. 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

  33. 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

  34. final def getInputSchema(): StructType

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

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

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    Definition Classes
    Params
  37. def getOutput(): FeatureLike[OPVector]

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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
    OpPipelineStageNOpPipelineStageBase
  38. 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
  39. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  40. 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
  41. final def getTransientFeatures(): Array[TransientFeature]

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    Gets the input Features

    Gets the input Features

    returns

    input features

    Definition Classes
    InputParams
  42. def getUnseenName: String

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    Definition Classes
    SaveOthersParams
  43. final def hasDefault[T](param: Param[T]): Boolean

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

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    Definition Classes
    Params
  45. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  46. final def inN: Array[TransientFeature]

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    Attributes
    protected
    Definition Classes
    HasInN
  47. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

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

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    Attributes
    protected
    Definition Classes
    Logging
  49. 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
    OpPipelineStageNInputParams
  50. final def isDefined(param: Param[_]): Boolean

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

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

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    Definition Classes
    Params
  53. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  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. def makeModel(topValues: Seq[Seq[String]], shouldCleanText: Boolean, shouldTrackNulls: Boolean, operationName: String, uid: String): OpTextPivotVectorizerModel[T]

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    Attributes
    protected
    Definition Classes
    OpTextPivotVectorizerOpOneHotVectorizer
  67. def makeVectorColumnMetadata(shouldTrackNulls: Boolean, unseen: Option[String], topValues: Seq[Seq[String]], features: Array[TransientFeature]): Array[OpVectorColumnMetadata]

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    Attributes
    protected
    Definition Classes
    OneHotFun
  68. def makeVectorMetadata(shouldTrackNulls: Boolean, unseen: Option[String], topValues: Seq[Seq[String]], outputName: String, features: Array[TransientFeature], stageName: String): OpVectorMetadata

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    Attributes
    protected
    Definition Classes
    OneHotFun
  69. final val minSupport: IntParam

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    Definition Classes
    MinSupportParam
  70. final def ne(arg0: AnyRef): Boolean

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

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

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    Definition Classes
    AnyRef
  73. def onGetMetadata(): Unit

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    Function to be called on getMetadata

    Function to be called on getMetadata

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

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    Function to be called on setInput

    Function to be called on setInput

    Definition Classes
    VectorizerDefaultsOpPipelineStageBase
  75. 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
    SequenceEstimatorOpPipelineStageBase
  76. 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
  77. def outputFeatureUid: String

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    Attributes
    protected[com.salesforce.op]
    Definition Classes
    OpPipelineStageNOpPipelineStage
  78. 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
  79. def outputVectorMeta: OpVectorMetadata

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    Get the metadata describing the output vector

    Get the metadata describing the output vector

    This does not trigger onGetMetadata()

    returns

    Metadata of output vector

    Attributes
    protected
    Definition Classes
    VectorizerDefaults
  80. lazy val params: Array[Param[_]]

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

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    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  82. val seqIConvert: FeatureTypeSparkConverter[T]

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    Definition Classes
    SequenceEstimator
  83. implicit val seqIEncoder: Encoder[Seq[T.Value]]

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    Definition Classes
    SequenceEstimator
  84. final def set(paramPair: ParamPair[_]): OpTextPivotVectorizer.this.type

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

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

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    Definition Classes
    Params
  87. def setCleanText(clean: Boolean): OpTextPivotVectorizer.this.type

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    Definition Classes
    TextParams
  88. final def setDefault(paramPairs: ParamPair[_]*): OpTextPivotVectorizer.this.type

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

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    Attributes
    protected
    Definition Classes
    Params
  90. final def setInput(features: FeatureLike[T]*): OpTextPivotVectorizer.this.type

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    Definition Classes
    OpPipelineStageN
  91. final def setInput(features: InputFeatures): OpTextPivotVectorizer.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
  92. final def setInputFeatures[S <: OPFeature](features: Array[S]): OpTextPivotVectorizer.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
  93. final def setMetadata(m: Metadata): OpTextPivotVectorizer.this.type

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    Definition Classes
    OpPipelineStageParams
  94. def setMinSupport(min: Int): OpTextPivotVectorizer.this.type

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    Definition Classes
    MinSupportParam
  95. def setOutputFeatureName(name: String): OpTextPivotVectorizer.this.type

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    Definition Classes
    OpPipelineStage
  96. def setTopK(numberToKeep: Int): OpTextPivotVectorizer.this.type

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    Definition Classes
    PivotParams
  97. def setTrackNulls(v: Boolean): OpTextPivotVectorizer.this.type

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    Option to keep track of values that were missing

    Option to keep track of values that were missing

    Definition Classes
    TrackNullsParam
  98. def setUnseenName(unseenNameIn: String): OpTextPivotVectorizer.this.type

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    Definition Classes
    SaveOthersParams
  99. 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
  100. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  101. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any
  102. final val topK: IntParam

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    Definition Classes
    PivotParams
  103. final val trackNulls: BooleanParam

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    Definition Classes
    TrackNullsParam
  104. 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
  105. def transformSchema(schema: StructType, logging: Boolean): StructType

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  106. implicit val tti: scala.reflect.api.JavaUniverse.TypeTag[T]

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    type tag for input

    type tag for input

    Definition Classes
    SequenceEstimator
  107. implicit val ttiv: scala.reflect.api.JavaUniverse.TypeTag[T.Value]

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    type tag for input value

    type tag for input value

    Definition Classes
    SequenceEstimator
  108. implicit val tto: scala.reflect.api.JavaUniverse.TypeTag[OPVector]

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    type tag for input

    type tag for input

    Definition Classes
    SequenceEstimatorOpPipelineStageN
  109. implicit val ttov: scala.reflect.api.JavaUniverse.TypeTag[Value]

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    type tag for output value

    type tag for output value

    Definition Classes
    SequenceEstimatorOpPipelineStageN
  110. val uid: String

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    uid for instance

    uid for instance

    Definition Classes
    SequenceEstimator → Identifiable
  111. final val unseenName: Param[String]

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    Definition Classes
    SaveOthersParams
  112. def vectorMetadataFromInputFeatures: OpVectorMetadata

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    Compute the output vector metadata only from the input features.

    Compute the output vector metadata only from the input features. Vectorizers use this to derive the full vector, including pivot columns or indicator features.

    returns

    Vector metadata from input features

    Attributes
    protected
    Definition Classes
    VectorizerDefaults
  113. def vectorMetadataWithNullIndicators: OpVectorMetadata

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    Attributes
    protected
    Definition Classes
    VectorizerDefaults
  114. def vectorOutputName: String

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    Get the name of the output vector

    Get the name of the output vector

    returns

    Output vector name as a string

    Attributes
    protected
    Definition Classes
    VectorizerDefaults
  115. final def wait(): Unit

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

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

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

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    Definition Classes
    OpPipelineStageBase → MLWritable

Inherited from OpOneHotVectorizer[T]

Inherited from OneHotFun

Inherited from MinSupportParam

Inherited from TrackNullsParam

Inherited from SaveOthersParams

Inherited from CleanTextFun

Inherited from PivotParams

Inherited from TextParams

Inherited from VectorizerDefaults

Inherited from SequenceEstimator[T, OPVector]

Inherited from OpPipelineStageN[T, OPVector]

Inherited from HasInN

Inherited from OpPipelineStage[OPVector]

Inherited from OpPipelineStageBase

Inherited from MLWritable

Inherited from OpPipelineStageParams

Inherited from InputParams

Inherited from Estimator[SequenceModel[T, OPVector]]

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