Class

com.salesforce.op.stages.impl.feature

OpCountVectorizer

Related Doc: package feature

Permalink

class OpCountVectorizer extends OpEstimatorWrapper[TextList, OPVector, CountVectorizer, CountVectorizerModel]

Wrapper around spark ml CountVectorizer for use with OP pipelines

Linear Supertypes
OpEstimatorWrapper[TextList, OPVector, CountVectorizer, CountVectorizerModel], SwUnaryEstimator[TextList, OPVector, CountVectorizerModel, CountVectorizer], SparkWrapperParams[CountVectorizer], OpPipelineStage1[TextList, OPVector], HasOut[OPVector], HasIn1, OpPipelineStage[OPVector], OpPipelineStageBase, MLWritable, OpPipelineStageParams, InputParams, Estimator[SwUnaryModel[TextList, OPVector, CountVectorizerModel]], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. OpCountVectorizer
  2. OpEstimatorWrapper
  3. SwUnaryEstimator
  4. SparkWrapperParams
  5. OpPipelineStage1
  6. HasOut
  7. HasIn1
  8. OpPipelineStage
  9. OpPipelineStageBase
  10. MLWritable
  11. OpPipelineStageParams
  12. InputParams
  13. Estimator
  14. PipelineStage
  15. Logging
  16. Params
  17. Serializable
  18. Serializable
  19. Identifiable
  20. AnyRef
  21. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

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

    Permalink

Type Members

  1. final type InputFeatures = FeatureLike[TextList]

    Permalink

    Input Features type

    Input Features type

    Definition Classes
    OpPipelineStage1OpPipelineStageInputParams
  2. final type OutputFeatures = FeatureLike[OPVector]

    Permalink
    Definition Classes
    OpPipelineStageOpPipelineStageBase

Value Members

  1. final def !=(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

    Permalink
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T

    Permalink
    Attributes
    protected
    Definition Classes
    Params
  4. final def ==(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  5. final def asInstanceOf[T0]: T0

    Permalink
    Definition Classes
    Any
  6. final def checkInputLength(features: Array[_]): Boolean

    Permalink

    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]

    Permalink

    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[_]): OpCountVectorizer.this.type

    Permalink
    Definition Classes
    Params
  9. def clone(): AnyRef

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  10. final def copy(extra: ParamMap): OpCountVectorizer.this.type

    Permalink

    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

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

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

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

    Permalink
    Definition Classes
    AnyRef → Any
  15. val estimator: CountVectorizer

    Permalink

    the estimator to wrap

    the estimator to wrap

    Definition Classes
    OpEstimatorWrapper
  16. def explainParam(param: Param[_]): String

    Permalink
    Definition Classes
    Params
  17. def explainParams(): String

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

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

    Permalink
    Definition Classes
    Params
  20. def finalize(): Unit

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  21. def fit(dataset: Dataset[_]): SwUnaryModel[TextList, OPVector, CountVectorizerModel]

    Permalink
    Definition Classes
    OpCountVectorizerSwUnaryEstimator → Estimator
  22. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[SwUnaryModel[TextList, OPVector, CountVectorizerModel]]

    Permalink
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  23. def fit(dataset: Dataset[_], paramMap: ParamMap): SwUnaryModel[TextList, OPVector, CountVectorizerModel]

    Permalink
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  24. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): SwUnaryModel[TextList, OPVector, CountVectorizerModel]

    Permalink
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  25. final def get[T](param: Param[T]): Option[T]

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

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

    Permalink
    Definition Classes
    Params
  28. def getInputColParamNames(): Array[String]

    Permalink

    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
  29. final def getInputFeature[T <: FeatureType](i: Int): Option[FeatureLike[T]]

    Permalink

    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]

    Permalink

    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

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

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

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

    Permalink

    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
  35. def getOutputColParamNames(): Array[String]

    Permalink

    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
  36. final def getOutputFeatureName: String

    Permalink

    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]

    Permalink
    Definition Classes
    Params
  38. def getSparkMlStage(): Option[CountVectorizer]

    Permalink

    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
  39. def getStageSavePath(): Option[String]

    Permalink

    Gets a save path for wrapped spark stage

    Gets a save path for wrapped spark stage

    Definition Classes
    SparkWrapperParams
  40. final def getTransientFeature(i: Int): Option[TransientFeature]

    Permalink

    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]

    Permalink

    Gets the input Features

    Gets the input Features

    returns

    input features

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

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

    Permalink
    Definition Classes
    Params
  44. def hashCode(): Int

    Permalink
    Definition Classes
    AnyRef → Any
  45. final def in1: TransientFeature

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

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

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  48. final def inputAsArray(in: InputFeatures): Array[OPFeature]

    Permalink

    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
  49. val inputParamName: String

    Permalink

    name of spark parameter that sets the second input column

    name of spark parameter that sets the second input column

    Definition Classes
    SwUnaryEstimator
  50. final def isDefined(param: Param[_]): Boolean

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

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

    Permalink
    Definition Classes
    Params
  53. def isTraceEnabled(): Boolean

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  54. def log: Logger

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

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

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

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

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

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

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  61. def logName: String

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

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

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

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

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

    Permalink
    Definition Classes
    AnyRef
  67. final def notify(): Unit

    Permalink
    Definition Classes
    AnyRef
  68. final def notifyAll(): Unit

    Permalink
    Definition Classes
    AnyRef
  69. def onGetMetadata(): Unit

    Permalink

    Function to be called on getMetadata

    Function to be called on getMetadata

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

    Permalink

    Function to be called on setInput

    Function to be called on setInput

    Attributes
    protected
    Definition Classes
    InputParams
  71. val operationName: String

    Permalink

    Short unique name of the operation this stage performs

    Short unique name of the operation this stage performs

    returns

    operation name

    Definition Classes
    OpCountVectorizerSwUnaryEstimatorOpPipelineStageBase
  72. final def outputAsArray(out: OutputFeatures): Array[OPFeature]

    Permalink

    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
  73. def outputFeatureUid: String

    Permalink
    Attributes
    protected[com.salesforce.op]
    Definition Classes
    OpPipelineStage1OpPipelineStage
  74. def outputIsResponse: Boolean

    Permalink

    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
  75. val outputParamName: String

    Permalink

    name of spark parameter that sets the first output column

    name of spark parameter that sets the first output column

    Definition Classes
    SwUnaryEstimator
  76. lazy val params: Array[Param[_]]

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

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

    Permalink
    Attributes
    protected
    Definition Classes
    Params
  79. final def set(param: String, value: Any): OpCountVectorizer.this.type

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

    Permalink
    Definition Classes
    Params
  81. def setBinary(value: Boolean): OpCountVectorizer.this.type

    Permalink

    Set binary toggle to control the output vector values.

    Set binary toggle to control the output vector values. If True, all nonzero counts (after minTF filter applied) are set to 1. This is useful for discrete probabilistic models that model binary events rather than integer counts. Default: false

  82. final def setDefault(paramPairs: ParamPair[_]*): OpCountVectorizer.this.type

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

    Permalink
    Attributes
    protected
    Definition Classes
    Params
  84. final def setInput(features: InputFeatures): OpCountVectorizer.this.type

    Permalink

    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
  85. final def setInputFeatures[S <: OPFeature](features: Array[S]): OpCountVectorizer.this.type

    Permalink

    Sets input features

    Sets input features

    S

    feature like type

    features

    array of input features

    returns

    this stage

    Attributes
    protected
    Definition Classes
    InputParams
  86. final def setMetadata(m: Metadata): OpCountVectorizer.this.type

    Permalink
    Definition Classes
    OpPipelineStageParams
  87. def setMinDF(value: Double): OpCountVectorizer.this.type

    Permalink

    Set minimum number of different documents a term must appear in to be included in the vocabulary.

    Set minimum number of different documents a term must appear in to be included in the vocabulary. If this is an integer greater than or equal to 1, this specifies the number of documents the term must appear in; if this is a double in [0,1), then this specifies the fraction of documents. Default: 1.0

  88. def setMinTF(value: Double): OpCountVectorizer.this.type

    Permalink

    Set minimum number of times a term must appear in a document.

    Set minimum number of times a term must appear in a document. Filter to ignore rare words in a document. For each document, terms with frequency/count less than the given threshold are ignored. If this is an integer greater than or equal to 1, then this specifies a count (of times the term must appear in the document); if this is a double in [0,1), then this specifies a fraction (out of the document's token count). Default: 1.0

  89. def setOutputFeatureName(name: String): OpCountVectorizer.this.type

    Permalink
    Definition Classes
    OpPipelineStage
  90. def setSparkMlStage(stage: Option[CountVectorizer]): OpCountVectorizer.this.type

    Permalink
    Attributes
    protected
    Definition Classes
    SparkWrapperParams
  91. def setStageSavePath(path: String): OpCountVectorizer.this.type

    Permalink

    Sets a save path for wrapped spark stage

    Sets a save path for wrapped spark stage

    Definition Classes
    SparkWrapperParams
  92. def setVocabSize(value: Int): OpCountVectorizer.this.type

    Permalink

    Set max size of the vocabulary.

    Set max size of the vocabulary. CountVectorizer will build a vocabulary that only considers the top vocabSize terms ordered by term frequency across the corpus. Default: 1 << 18

  93. final val sparkInputColParamNames: StringArrayParam

    Permalink
    Definition Classes
    SparkWrapperParams
  94. final val sparkMlStage: SparkStageParam[CountVectorizer]

    Permalink
    Definition Classes
    SparkWrapperParams
  95. final val sparkOutputColParamNames: StringArrayParam

    Permalink
    Definition Classes
    SparkWrapperParams
  96. final def stageName: String

    Permalink

    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
  97. final def synchronized[T0](arg0: ⇒ T0): T0

    Permalink
    Definition Classes
    AnyRef
  98. def toString(): String

    Permalink
    Definition Classes
    Identifiable → AnyRef → Any
  99. final def transformSchema(schema: StructType): StructType

    Permalink

    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
  100. def transformSchema(schema: StructType, logging: Boolean): StructType

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

    Permalink

    type tag for input

    type tag for input

    Definition Classes
    SwUnaryEstimator
  102. implicit val tto: scala.reflect.api.JavaUniverse.TypeTag[OPVector]

    Permalink

    type tag for output

    type tag for output

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

    Permalink

    type tag for output value

    type tag for output value

    Definition Classes
    SwUnaryEstimator → HasOut
  104. val uid: String

    Permalink

    stage uid

    stage uid

    Definition Classes
    SwUnaryEstimator → Identifiable
  105. final def wait(): Unit

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

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

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

    Permalink
    Definition Classes
    OpPipelineStageBase → MLWritable

Inherited from OpEstimatorWrapper[TextList, OPVector, CountVectorizer, CountVectorizerModel]

Inherited from SwUnaryEstimator[TextList, OPVector, CountVectorizerModel, CountVectorizer]

Inherited from SparkWrapperParams[CountVectorizer]

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 Estimator[SwUnaryModel[TextList, OPVector, CountVectorizerModel]]

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

setParam

Ungrouped