Class

com.salesforce.op.stages.impl.feature

TextMapPivotVectorizer

Related Doc: package feature

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class TextMapPivotVectorizer[T <: OPMap[String]] extends SequenceEstimator[T, OPVector] with PivotParams with MapPivotParams with TextParams with MapStringPivotHelper with CleanTextMapFun with MinSupportParam with TrackNullsParam with MaxPctCardinalityParams with MaxPctCardinalityFun

Converts a sequence of KeyString features into a vector keeping the top K most common occurrences of each key in the maps for that feature (ie the final vector has length k * number of keys * number of features). Each key found will also generate an other column which will capture values that do not make the cut or where not seen in training. Note that any keys not seen in training will be ignored.

Linear Supertypes
MaxPctCardinalityFun, UniqueCountFun, MaxPctCardinalityParams, TrackNullsParam, MinSupportParam, CleanTextMapFun, CleanTextFun, MapStringPivotHelper, SaveOthersParams, MapPivotParams, PivotParams, TextParams, SequenceEstimator[T, OPVector], OpPipelineStageN[T, OPVector], HasOut[OPVector], HasInN, OpPipelineStage[OPVector], OpPipelineStageBase, MLWritable, OpPipelineStageParams, InputParams, Estimator[SequenceModel[T, OPVector]], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. TextMapPivotVectorizer
  2. MaxPctCardinalityFun
  3. UniqueCountFun
  4. MaxPctCardinalityParams
  5. TrackNullsParam
  6. MinSupportParam
  7. CleanTextMapFun
  8. CleanTextFun
  9. MapStringPivotHelper
  10. SaveOthersParams
  11. MapPivotParams
  12. PivotParams
  13. TextParams
  14. SequenceEstimator
  15. OpPipelineStageN
  16. HasOut
  17. HasInN
  18. OpPipelineStage
  19. OpPipelineStageBase
  20. MLWritable
  21. OpPipelineStageParams
  22. InputParams
  23. Estimator
  24. PipelineStage
  25. Logging
  26. Params
  27. Serializable
  28. Serializable
  29. Identifiable
  30. AnyRef
  31. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new TextMapPivotVectorizer(uid: String = UID[TextMapPivotVectorizer[T]])(implicit tti: scala.reflect.api.JavaUniverse.TypeTag[T])

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    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. type MapMap = Map[String, Map[String, Long]]

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    Definition Classes
    MapStringPivotHelper
  3. final type OutputFeatures = FeatureLike[OPVector]

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    Definition Classes
    OpPipelineStageOpPipelineStageBase
  4. type SeqMapMap = Seq[utils.spark.SequenceAggregators.MapMap]

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    Definition Classes
    MapStringPivotHelper
  5. type SeqSeqTupArr = Seq[Seq[(String, Array[String])]]

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    Definition Classes
    MapStringPivotHelper

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 val blackListKeys: StringArrayParam

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    Definition Classes
    MapPivotParams
  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 cleanKeys: BooleanParam

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    Definition Classes
    MapPivotParams
  10. def cleanMap[V](m: Map[String, V], shouldCleanKey: Boolean, shouldCleanValue: Boolean): Map[String, V]

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    Definition Classes
    CleanTextMapFun
  11. final val cleanText: BooleanParam

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

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

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    Definition Classes
    Params
  14. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  15. final def copy(extra: ParamMap): TextMapPivotVectorizer.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
  16. def copyValues[T <: Params](to: T, extra: ParamMap): T

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    Attributes
    protected
    Definition Classes
    Params
  17. def countMapUniques[V](dataset: Dataset[Seq[Map[String, V]]], size: Int, bits: Int)(implicit kryo: KryoSerializer, ct: ClassTag[V]): (Seq[Map[String, HLL]], Long)

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    Count unique values of each of the sequence & map key components in the dataset using HyperLogLog HLL

    Count unique values of each of the sequence & map key components in the dataset using HyperLogLog HLL

    V

    value type

    dataset

    dataset to count unique values

    size

    size of each sequence component

    bits

    number of bits for HyperLogLog HLL

    kryo

    kryo serializer to serialize V value into array of bytes

    ct

    class tag of V - needed by kryo

    returns

    HyperLogLog HLL of unique values count for each of the sequence components and total rows count

    Definition Classes
    UniqueCountFun
  18. def countUniques[V](dataset: Dataset[Seq[V]], size: Int, bits: Int)(implicit kryo: KryoSerializer, ct: ClassTag[V]): (Seq[HLL], Long)

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    Count unique values of each of the sequence components in the dataset using HyperLogLog HLL

    Count unique values of each of the sequence components in the dataset using HyperLogLog HLL

    V

    value type

    dataset

    dataset to count unique values

    size

    size of each sequence component

    bits

    number of bits for HyperLogLog HLL

    kryo

    kryo serializer to serialize V value into array of bytes

    ct

    class tag of V - needed by kryo

    returns

    HyperLogLog HLL of unique values count for each of the sequence components and total rows count

    Definition Classes
    UniqueCountFun
  19. final def defaultCopy[T <: Params](extra: ParamMap): T

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

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

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

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    Definition Classes
    Params
  23. def explainParams(): String

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

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

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    Definition Classes
    Params
  26. def filterByMaxCardinality[V](dataset: Dataset[Seq[Map[String, V]]], maxPctCardinality: Double, size: Int, bits: Int)(implicit tt: scala.reflect.api.JavaUniverse.TypeTag[V], enc: Encoder[Seq[Map[String, V]]]): Dataset[Seq[Map[String, V]]]

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    Throw out values above max percent cardinality as follows:

    Throw out values above max percent cardinality as follows:

    1. count unique values of each of the sequence & map key components in the dataset using HyperLogLog HLL 2. count total number of rows 3. compute percent filters for each of the sequence & map key components 4. throw out values above max percent cardinality

    V

    value type

    dataset

    dataset to count unique values

    maxPctCardinality

    max percentage of distinct values a categorical feature can have

    size

    size of each sequence component

    bits

    number of bits for HyperLogLog HLL

    tt

    type tag of V - needed by kryo

    enc

    values encoder for dataset

    Definition Classes
    MaxPctCardinalityFun
  27. def filterKeys[V](m: Map[String, V], shouldCleanKey: Boolean, shouldCleanValue: Boolean): Map[String, V]

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    Attributes
    protected
    Definition Classes
    MapPivotParams
  28. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  29. 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
  30. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[SequenceModel[T, OPVector]]

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

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

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

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    Function that fits the sequence model

    Function that fits the sequence model

    Definition Classes
    TextMapPivotVectorizerSequenceEstimator
  34. final def get[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  35. def getCategoryMaps[V](in: Dataset[Seq[Map[String, V]]], convertToMapOfMaps: (Map[String, V]) ⇒ MapMap, shouldCleanKeys: Boolean, shouldCleanValues: Boolean): Dataset[SeqMapMap]

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    Attributes
    protected
    Definition Classes
    MapStringPivotHelper
  36. final def getClass(): Class[_]

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

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    Definition Classes
    Params
  38. final def getHLLBits: Int

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    Definition Classes
    MaxPctCardinalityParams
  39. 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

  40. 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

  41. final def getInputSchema(): StructType

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    Definition Classes
    OpPipelineStageParams
  42. final def getMaxPctCardinality: Double

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    Definition Classes
    MaxPctCardinalityParams
  43. final def getMetadata(): Metadata

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

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    Definition Classes
    Params
  45. 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
    HasOut → OpPipelineStageBase
  46. 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
  47. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  48. def getTopValues(categoryMaps: Dataset[SeqMapMap], inputSize: Int, topK: Int, minSup: Int): SeqSeqTupArr

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    Attributes
    protected
    Definition Classes
    MapStringPivotHelper
  49. 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
  50. final def getTransientFeatures(): Array[TransientFeature]

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    Gets the input Features

    Gets the input Features

    returns

    input features

    Definition Classes
    InputParams
  51. def getUnseenName: String

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

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

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    Definition Classes
    Params
  54. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  55. final val hllBits: IntParam

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    Definition Classes
    MaxPctCardinalityParams
  56. final def inN: Array[TransientFeature]

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  59. 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
  60. final def isDefined(param: Param[_]): Boolean

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

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

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    Definition Classes
    Params
  63. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  64. def log: Logger

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

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  71. def logName: String

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  76. def makeOutputVectorMetadata(topValues: SeqSeqTupArr, inputFeatures: Array[TransientFeature], operationName: String, outputName: String, stageName: String, trackNulls: Boolean = false): OpVectorMetadata

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    Attributes
    protected
    Definition Classes
    MapStringPivotHelper
  77. def makeVectorColumnMetadata(topValues: SeqSeqTupArr, inputFeatures: Array[TransientFeature], unseenName: String, trackNulls: Boolean = false): Array[OpVectorColumnMetadata]

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    Attributes
    protected
    Definition Classes
    MapStringPivotHelper
  78. final val maxPctCardinality: DoubleParam

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    Definition Classes
    MaxPctCardinalityParams
  79. final val minSupport: IntParam

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

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

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

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    Definition Classes
    AnyRef
  83. def onGetMetadata(): Unit

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    Function to be called on getMetadata

    Function to be called on getMetadata

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

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    Function to be called on setInput

    Function to be called on setInput

    Attributes
    protected
    Definition Classes
    InputParams
  85. 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
  86. 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
  87. def outputFeatureUid: String

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    Attributes
    protected[com.salesforce.op]
    Definition Classes
    OpPipelineStageNOpPipelineStage
  88. 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
  89. lazy val params: Array[Param[_]]

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

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

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

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

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

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

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    Definition Classes
    Params
  96. final def setBlackListKeys(keys: Array[String]): TextMapPivotVectorizer.this.type

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    Definition Classes
    MapPivotParams
  97. def setCleanKeys(clean: Boolean): TextMapPivotVectorizer.this.type

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    Definition Classes
    MapPivotParams
  98. def setCleanText(clean: Boolean): TextMapPivotVectorizer.this.type

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

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

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    Attributes
    protected
    Definition Classes
    Params
  101. final def setHLLBits(value: Int): TextMapPivotVectorizer.this.type

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    Definition Classes
    MaxPctCardinalityParams
  102. final def setInput(features: FeatureLike[T]*): TextMapPivotVectorizer.this.type

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    Definition Classes
    OpPipelineStageN
  103. final def setInput(features: InputFeatures): TextMapPivotVectorizer.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
  104. final def setInputFeatures[S <: OPFeature](features: Array[S]): TextMapPivotVectorizer.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
  105. final def setMaxPctCardinality(v: Double): TextMapPivotVectorizer.this.type

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    Definition Classes
    MaxPctCardinalityParams
  106. final def setMetadata(m: Metadata): TextMapPivotVectorizer.this.type

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    Definition Classes
    OpPipelineStageParams
  107. def setMinSupport(min: Int): TextMapPivotVectorizer.this.type

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    Definition Classes
    MinSupportParam
  108. def setOutputFeatureName(name: String): TextMapPivotVectorizer.this.type

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    Definition Classes
    OpPipelineStage
  109. def setTopK(numberToKeep: Int): TextMapPivotVectorizer.this.type

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    Definition Classes
    PivotParams
  110. def setTrackNulls(v: Boolean): TextMapPivotVectorizer.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
  111. def setUnseenName(unseenNameIn: String): TextMapPivotVectorizer.this.type

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    Definition Classes
    SaveOthersParams
  112. final def setWhiteListKeys(keys: Array[String]): TextMapPivotVectorizer.this.type

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    Definition Classes
    MapPivotParams
  113. 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
  114. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  115. def toString(): String

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

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    Definition Classes
    PivotParams
  117. final val trackNulls: BooleanParam

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    Definition Classes
    TrackNullsParam
  118. 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
  119. def transformSchema(schema: StructType, logging: Boolean): StructType

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

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    type tag for input

    type tag for input

    Definition Classes
    SequenceEstimator
  121. 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
  122. implicit val tto: scala.reflect.api.JavaUniverse.TypeTag[OPVector]

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    type tag for input

    type tag for input

    Definition Classes
    SequenceEstimator → HasOut
  123. 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
    SequenceEstimator → HasOut
  124. val uid: String

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    uid for instance

    uid for instance

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

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    Definition Classes
    SaveOthersParams
  126. final def wait(): Unit

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

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  129. final val whiteListKeys: StringArrayParam

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    Definition Classes
    MapPivotParams
  130. final def write: MLWriter

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    Definition Classes
    OpPipelineStageBase → MLWritable

Inherited from MaxPctCardinalityFun

Inherited from UniqueCountFun

Inherited from MaxPctCardinalityParams

Inherited from TrackNullsParam

Inherited from MinSupportParam

Inherited from CleanTextMapFun

Inherited from CleanTextFun

Inherited from MapStringPivotHelper

Inherited from SaveOthersParams

Inherited from MapPivotParams

Inherited from PivotParams

Inherited from TextParams

Inherited from SequenceEstimator[T, OPVector]

Inherited from OpPipelineStageN[T, OPVector]

Inherited from HasOut[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