Class

com.salesforce.op.stages.impl.feature

OpHashingTF

Related Doc: package feature

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class OpHashingTF extends OpTransformerWrapper[TextList, OPVector, HashingTF]

Wrapper for org.apache.spark.ml.feature.HashingTF

Maps a sequence of terms to their term frequencies using the hashing trick. Currently we use Austin Appleby's MurmurHash 3 algorithm (MurmurHash3_x86_32) to calculate the hash code value for the term object. Since a simple modulo is used to transform the hash function to a column index, it is advisable to use a power of two as the numFeatures parameter; otherwise the features will not be mapped evenly to the columns.

See also

HashingTF for more info

Linear Supertypes
OpTransformerWrapper[TextList, OPVector, HashingTF], SwUnaryTransformer[TextList, OPVector, HashingTF], SwTransformer1[TextList, OPVector, HashingTF], SparkWrapperParams[HashingTF], OpPipelineStage1[TextList, OPVector], HasOut[OPVector], HasIn1, OpPipelineStage[OPVector], OpPipelineStageBase, MLWritable, OpPipelineStageParams, InputParams, Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. OpHashingTF
  2. OpTransformerWrapper
  3. SwUnaryTransformer
  4. SwTransformer1
  5. SparkWrapperParams
  6. OpPipelineStage1
  7. HasOut
  8. HasIn1
  9. OpPipelineStage
  10. OpPipelineStageBase
  11. MLWritable
  12. OpPipelineStageParams
  13. InputParams
  14. Transformer
  15. PipelineStage
  16. Logging
  17. Params
  18. Serializable
  19. Serializable
  20. Identifiable
  21. AnyRef
  22. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new OpHashingTF(uid: String = UID[HashingTF])

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Type Members

  1. final type InputFeatures = FeatureLike[TextList]

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    Input Features type

    Input Features type

    Definition Classes
    OpPipelineStage1OpPipelineStageInputParams
  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. 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
    OpPipelineStage1InputParams
  7. 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
    OpPipelineStageBase
  8. final def clear(param: Param[_]): OpHashingTF.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): OpHashingTF.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 explainParam(param: Param[_]): String

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    Definition Classes
    Params
  16. def explainParams(): String

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

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

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    Definition Classes
    Params
  19. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  20. final def get[T](param: Param[T]): Option[T]

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

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

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    Definition Classes
    Params
  23. 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
  24. 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

  25. 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

  26. final def getInputSchema(): StructType

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

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

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    Definition Classes
    Params
  29. 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
  30. 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
  31. 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
  32. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  33. def getSparkMlStage(): Option[HashingTF]

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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
  34. 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
  35. 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
  36. final def getTransientFeatures(): Array[TransientFeature]

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    Gets the input Features

    Gets the input Features

    returns

    input features

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

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

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    Definition Classes
    Params
  39. def hashCode(): Int

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

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    Attributes
    protected
    Definition Classes
    HasIn1
  41. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

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

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    Attributes
    protected
    Definition Classes
    Logging
  43. 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
    OpPipelineStage1InputParams
  44. val inputParamName: String

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    name of spark parameter that sets the first input column

    name of spark parameter that sets the first input column

    Definition Classes
    SwUnaryTransformer → SwTransformer1
  45. final def isDefined(param: Param[_]): Boolean

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

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

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    Definition Classes
    Params
  48. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  49. def log: Logger

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

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  56. def logName: String

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

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

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

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

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

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

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

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    Definition Classes
    AnyRef
  64. def onGetMetadata(): Unit

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    Function to be called on getMetadata

    Function to be called on getMetadata

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

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    Function to be called on setInput

    Function to be called on setInput

    Attributes
    protected
    Definition Classes
    InputParams
  66. 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
    SwUnaryTransformerOpPipelineStageBase
  67. 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
  68. def outputFeatureUid: String

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    Attributes
    protected[com.salesforce.op]
    Definition Classes
    OpPipelineStage1OpPipelineStage
  69. 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
  70. val outputParamName: String

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    name of spark parameter that sets the first output column

    name of spark parameter that sets the first output column

    Definition Classes
    SwUnaryTransformer → SwTransformer1
  71. lazy val params: Array[Param[_]]

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

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

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

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

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    Definition Classes
    Params
  76. def setBinary(value: Boolean): OpHashingTF.this.type

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    Binary toggle to control term frequency counts.

    Binary toggle to control term frequency counts. If true, all non-zero counts are set to 1. This is useful for discrete probabilistic models that model binary events rather than integer counts. (default = false)

  77. final def setDefault(paramPairs: ParamPair[_]*): OpHashingTF.this.type

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

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

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    Definition Classes
    OpPipelineStageParams
  82. def setNumFeatures(value: Int): OpHashingTF.this.type

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    Number of features.

    Number of features. Should be greater than 0. (default = 218)

  83. def setOutputFeatureName(name: String): OpHashingTF.this.type

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    Definition Classes
    OpPipelineStage
  84. def setSparkMlStage(stage: Option[HashingTF]): OpHashingTF.this.type

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    Attributes
    protected
    Definition Classes
    SparkWrapperParams
  85. def setStageSavePath(path: String): OpHashingTF.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
  86. final val sparkInputColParamNames: StringArrayParam

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    Definition Classes
    SparkWrapperParams
  87. final val sparkMlStage: SparkStageParam[HashingTF]

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    Definition Classes
    SparkWrapperParams
  88. final val sparkOutputColParamNames: StringArrayParam

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    Definition Classes
    SparkWrapperParams
  89. 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
  90. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  91. def toString(): String

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

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    Definition Classes
    SwTransformer1 → Transformer
  93. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

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

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  95. 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
  96. def transformSchema(schema: StructType, logging: Boolean): StructType

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  97. val transformer: HashingTF

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    The spark ML transformer that's being wrapped

    The spark ML transformer that's being wrapped

    Definition Classes
    OpTransformerWrapper
  98. implicit val tti: scala.reflect.api.JavaUniverse.TypeTag[TextList]

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    Definition Classes
    SwUnaryTransformer → SwTransformer1
  99. implicit val tto: scala.reflect.api.JavaUniverse.TypeTag[OPVector]

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    Type tag of the output

    Type tag of the output

    Definition Classes
    SwUnaryTransformer → HasOut
  100. implicit val ttov: scala.reflect.api.JavaUniverse.TypeTag[Value]

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    Type tag of the output value

    Type tag of the output value

    Definition Classes
    SwUnaryTransformer → HasOut
  101. val uid: String

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    stage uid

    stage uid

    Definition Classes
    SwUnaryTransformer → Identifiable
  102. final def wait(): Unit

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

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

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

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    Definition Classes
    OpPipelineStageBase → MLWritable

Inherited from OpTransformerWrapper[TextList, OPVector, HashingTF]

Inherited from SwUnaryTransformer[TextList, OPVector, HashingTF]

Inherited from SwTransformer1[TextList, OPVector, HashingTF]

Inherited from SparkWrapperParams[HashingTF]

Inherited from HasOut[OPVector]

Inherited from HasIn1

Inherited from OpPipelineStage[OPVector]

Inherited from OpPipelineStageBase

Inherited from MLWritable

Inherited from OpPipelineStageParams

Inherited from InputParams

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