Class

com.salesforce.op.stages.impl.feature

OPCollectionHashingVectorizer

Related Doc: package feature

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class OPCollectionHashingVectorizer[T <: OPCollection] extends SequenceTransformer[T, OPVector] with VectorizerDefaults with PivotParams with CleanTextFun with HashingFun with HashingVectorizerParams

Generic hashing vectorizer to convert features of type OPCollection into Vectors

In more details: It tries to hash entries in the collection using the specified hashing algorithm to build a single vector. If the desired number of features (= hash space size) for all features combined is larger than Integer.Max (the maximal index for a vector), then all the features use the same hash space. There are also options for the user to hash indices with collections where that makes sense (OPLists and OPVectors), and to force a shared hash space, even if the number of feature is not high enough to require it.

Linear Supertypes
HashingVectorizerParams, HashingFun, CleanTextFun, PivotParams, TextParams, VectorizerDefaults, SequenceTransformer[T, OPVector], OpTransformerN[T, OPVector], OpTransformer, OpPipelineStageN[T, OPVector], HasInN, OpPipelineStage[OPVector], OpPipelineStageBase, MLWritable, OpPipelineStageParams, InputParams, Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. OPCollectionHashingVectorizer
  2. HashingVectorizerParams
  3. HashingFun
  4. CleanTextFun
  5. PivotParams
  6. TextParams
  7. VectorizerDefaults
  8. SequenceTransformer
  9. OpTransformerN
  10. OpTransformer
  11. OpPipelineStageN
  12. HasInN
  13. OpPipelineStage
  14. OpPipelineStageBase
  15. MLWritable
  16. OpPipelineStageParams
  17. InputParams
  18. Transformer
  19. PipelineStage
  20. Logging
  21. Params
  22. Serializable
  23. Serializable
  24. Identifiable
  25. AnyRef
  26. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new OPCollectionHashingVectorizer(uid: String = ...)(implicit tti: scala.reflect.api.JavaUniverse.TypeTag[T], ttvi: scala.reflect.api.JavaUniverse.TypeTag[T.Value])

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    uid

    uid of the stage

Type Members

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

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    Input Features type

    Input Features type

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

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

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

    Definition Classes
    OpTransformer
  3. final type OutputFeatures = FeatureLike[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 val binaryFreq: BooleanParam

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    Definition Classes
    HashingVectorizerParams
  7. implicit def booleanToDouble(v: Boolean): Double

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    Definition Classes
    VectorizerDefaults
  8. 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
  9. 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
    OpTransformerNOpPipelineStageBase
  10. final val cleanText: BooleanParam

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

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

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    Definition Classes
    Params
  13. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  14. final def copy(extra: ParamMap): OPCollectionHashingVectorizer.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. final def get[T](param: Param[T]): Option[T]

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

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

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    Definition Classes
    Params
  27. def getHashAlgorithm: HashAlgorithm

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    Definition Classes
    HashingVectorizerParams
  28. def getHashSpaceStrategy: HashSpaceStrategy

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    Definition Classes
    HashingVectorizerParams
  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. def getNumFeatures(): Int

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    Definition Classes
    HashingVectorizerParams
  34. final def getOrDefault[T](param: Param[T]): T

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    Definition Classes
    Params
  35. 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
  36. 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
  37. def getParam(paramName: String): Param[Any]

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

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    Gets an input feature at index i

    Gets an input feature at index i

    i

    input index

    returns

    maybe an input feature

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

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    Gets the input Features

    Gets the input Features

    returns

    input features

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

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

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    Definition Classes
    Params
  42. def hash[T <: OPCollection](in: Seq[T], features: Array[TransientFeature], params: HashingFunctionParams): OPVector

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    Hashes input sequence of values into OPVector using the supplied hashing params

    Hashes input sequence of values into OPVector using the supplied hashing params

    Attributes
    protected
    Definition Classes
    HashingFun
  43. final val hashAlgorithm: Param[String]

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    Definition Classes
    HashingVectorizerParams
  44. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  45. final val hashSpaceStrategy: Param[String]

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    Definition Classes
    HashingVectorizerParams
  46. final val hashWithIndex: BooleanParam

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    Definition Classes
    HashingVectorizerParams
  47. def hashingTF(): HashingTF

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    Get the underlying hashing transformer

    Get the underlying hashing transformer

    returns

    HashingTF

  48. def hashingTF(params: HashingFunctionParams): HashingTF

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    HashingTF instance

    HashingTF instance

    Attributes
    protected
    Definition Classes
    HashingFun
  49. final def inN: Array[TransientFeature]

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  52. 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
  53. final def isDefined(param: Param[_]): Boolean

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

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

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    Definition Classes
    Params
  56. def isSharedHashSpace: Boolean

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    Determine if the transformer should use a shared hash space for all features or not

    Determine if the transformer should use a shared hash space for all features or not

    returns

    true if the shared hashing space to be used, false otherwise

  57. def isSharedHashSpace(p: HashingFunctionParams, numFeatures: Option[Int] = None): Boolean

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    Determine if the transformer should use a shared hash space for all features or not

    Determine if the transformer should use a shared hash space for all features or not

    returns

    true if the shared hashing space to be used, false otherwise

    Attributes
    protected
    Definition Classes
    HashingFun
  58. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  59. def log: Logger

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

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  66. def logName: String

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  71. def makeHashingParams(): HashingFunctionParams

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    Attributes
    protected
  72. def makeVectorColumnMetadata(features: Array[TransientFeature], params: HashingFunctionParams): Array[OpVectorColumnMetadata]

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    Attributes
    protected
    Definition Classes
    HashingFun
  73. def makeVectorMetadata(features: Array[TransientFeature], params: HashingFunctionParams, outputName: String): OpVectorMetadata

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    Attributes
    protected
    Definition Classes
    HashingFun
  74. final def ne(arg0: AnyRef): Boolean

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

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

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    Definition Classes
    AnyRef
  77. final val numFeatures: IntParam

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    Definition Classes
    HashingVectorizerParams
  78. def onGetMetadata(): Unit

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    Function to be called on getMetadata

    Function to be called on getMetadata

    Definition Classes
    OPCollectionHashingVectorizerOpPipelineStageParams
  79. def onSetInput(): Unit

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    Function to be called on setInput

    Function to be called on setInput

    Definition Classes
    VectorizerDefaultsOpPipelineStageBase
  80. 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
    SequenceTransformerOpPipelineStageBase
  81. 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
  82. def outputFeatureUid: String

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    Attributes
    protected[com.salesforce.op]
    Definition Classes
    OpPipelineStageNOpPipelineStage
  83. 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
  84. 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
  85. lazy val params: Array[Param[_]]

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    Definition Classes
    Params
  86. def prepare[T <: OPCollection](el: T, shouldHashWithIndex: Boolean, shouldPrependFeatureName: Boolean, featureNameHash: Int): Iterable[Any]

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    Function that prepares the input columns to be hashed Note that MurMur3 hashing algorithm only defined for primitive types so need to convert tuples to strings.

    Function that prepares the input columns to be hashed Note that MurMur3 hashing algorithm only defined for primitive types so need to convert tuples to strings. MultiPickList sets are hashed as is since there is no meaningful order in the selected choices. Lists and vectors can be hashed with or without their indices, since order may be important. Maps are hashed as (key,value) strings.

    el

    element we are hashing (eg. an OPList, OPMap, etc.)

    returns

    an Iterable object corresponding to the hashed element

    Attributes
    protected
    Definition Classes
    HashingFun
  87. final val prependFeatureName: BooleanParam

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    Definition Classes
    HashingVectorizerParams
  88. def save(path: String): Unit

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

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

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

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    Definition Classes
    Params
  92. def setBinaryFreq(v: Boolean): OPCollectionHashingVectorizer.this.type

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    Definition Classes
    HashingVectorizerParams
  93. def setCleanText(clean: Boolean): OPCollectionHashingVectorizer.this.type

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

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

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    Attributes
    protected
    Definition Classes
    Params
  96. def setHashAlgorithm(h: HashAlgorithm): OPCollectionHashingVectorizer.this.type

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    Definition Classes
    HashingVectorizerParams
  97. def setHashSpaceStrategy(v: HashSpaceStrategy): OPCollectionHashingVectorizer.this.type

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    Definition Classes
    HashingVectorizerParams
  98. def setHashWithIndex(v: Boolean): OPCollectionHashingVectorizer.this.type

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    Definition Classes
    HashingVectorizerParams
  99. final def setInput(features: FeatureLike[T]*): OPCollectionHashingVectorizer.this.type

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    Definition Classes
    OpPipelineStageN
  100. final def setInput(features: InputFeatures): OPCollectionHashingVectorizer.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
  101. final def setInputFeatures[S <: OPFeature](features: Array[S]): OPCollectionHashingVectorizer.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
  102. final def setMetadata(m: Metadata): OPCollectionHashingVectorizer.this.type

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    Definition Classes
    OpPipelineStageParams
  103. def setNumFeatures(v: Int): OPCollectionHashingVectorizer.this.type

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    Definition Classes
    HashingVectorizerParams
  104. def setOutputFeatureName(name: String): OPCollectionHashingVectorizer.this.type

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    Definition Classes
    OpPipelineStage
  105. def setPrependFeatureName(v: Boolean): OPCollectionHashingVectorizer.this.type

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    Definition Classes
    HashingVectorizerParams
  106. def setTopK(numberToKeep: Int): OPCollectionHashingVectorizer.this.type

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    Definition Classes
    PivotParams
  107. 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
  108. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  109. def toString(): String

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

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    Definition Classes
    PivotParams
  111. def transform(dataset: Dataset[_]): DataFrame

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

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

    dataset

    input data for this stage

    returns

    a new dataset containing a column for the transformed feature

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

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

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  114. def transformFn: (Seq[T]) ⇒ OPVector

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    Function used to convert input to output

    Function used to convert input to output

    Definition Classes
    OPCollectionHashingVectorizerOpTransformerN
  115. lazy val transformKeyValue: (KeyValue) ⇒ Any

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

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

    returns

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

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

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    Creates a transform function to transform Map to a value

    Creates a transform function to transform Map to a value

    returns

    a transform function to transform Map to a value

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

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    Creates a transform function to transform Row to a value

    Creates a transform function to transform Row to a value

    returns

    a transform function to transform Row to a value

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

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    type tag for output

    type tag for output

    Definition Classes
    SequenceTransformerOpPipelineStageN
  122. 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
    SequenceTransformerOpPipelineStageN
  123. implicit val ttvi: scala.reflect.api.JavaUniverse.TypeTag[T.Value]

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  124. val uid: String

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    uid for instance

    uid for instance

    Definition Classes
    SequenceTransformer → Identifiable
  125. 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
  126. def vectorMetadataWithNullIndicators: OpVectorMetadata

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    Attributes
    protected
    Definition Classes
    VectorizerDefaults
  127. 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
  128. final def wait(): Unit

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

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

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

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    Definition Classes
    OpPipelineStageBase → MLWritable

Inherited from HashingVectorizerParams

Inherited from HashingFun

Inherited from CleanTextFun

Inherited from PivotParams

Inherited from TextParams

Inherited from VectorizerDefaults

Inherited from SequenceTransformer[T, OPVector]

Inherited from OpTransformerN[T, OPVector]

Inherited from OpTransformer

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 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