Class/Object

com.salesforce.op.stages.impl.feature

SmartTextVectorizer

Related Docs: object SmartTextVectorizer | package feature

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class SmartTextVectorizer[T <: Text] extends SequenceEstimator[T, OPVector] with PivotParams with CleanTextFun with SaveOthersParams with TrackNullsParam with MinSupportParam with TextTokenizerParams with HashingVectorizerParams with HashingFun with OneHotFun with MaxCardinalityParams

Convert a sequence of text features into a vector by detecting categoricals that are disguised as text. A categorical will be represented as a vector consisting of occurrences of top K most common values of that feature plus occurrences of non top k values and a null indicator (if enabled). Non-categoricals will be converted into a vector using the hashing trick. In addition, a null indicator is created for each non-categorical (if enabled).

Linear Supertypes
MaxCardinalityParams, OneHotFun, HashingFun, HashingVectorizerParams, TextTokenizerParams, LanguageDetectionParams, MinSupportParam, TrackNullsParam, SaveOthersParams, CleanTextFun, PivotParams, TextParams, SequenceEstimator[T, OPVector], OpPipelineStageN[T, 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. SmartTextVectorizer
  2. MaxCardinalityParams
  3. OneHotFun
  4. HashingFun
  5. HashingVectorizerParams
  6. TextTokenizerParams
  7. LanguageDetectionParams
  8. MinSupportParam
  9. TrackNullsParam
  10. SaveOthersParams
  11. CleanTextFun
  12. PivotParams
  13. TextParams
  14. SequenceEstimator
  15. OpPipelineStageN
  16. HasInN
  17. OpPipelineStage
  18. OpPipelineStageBase
  19. MLWritable
  20. OpPipelineStageParams
  21. InputParams
  22. Estimator
  23. PipelineStage
  24. Logging
  25. Params
  26. Serializable
  27. Serializable
  28. Identifiable
  29. AnyRef
  30. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new SmartTextVectorizer(uid: String = UID[SmartTextVectorizer[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. 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 autoDetectLanguage: BooleanParam

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    Indicates whether to attempt language detection.

    Indicates whether to attempt language detection.

    Definition Classes
    LanguageDetectionParams
  7. final val autoDetectThreshold: DoubleParam

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    Language detection threshold.

    Language detection threshold. If none of the detected languages have confidence greater than the threshold then defaultLanguage is used.

    Definition Classes
    LanguageDetectionParams
  8. final val binaryFreq: BooleanParam

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    Definition Classes
    HashingVectorizerParams
  9. 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
  10. 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
  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[_]): SmartTextVectorizer.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): SmartTextVectorizer.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. final def defaultCopy[T <: Params](extra: ParamMap): T

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    Attributes
    protected
    Definition Classes
    Params
  18. final val defaultLanguage: Param[String]

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    Default language to assume in case autoDetectLanguage is disabled or failed to make a good enough prediction.

    Default language to assume in case autoDetectLanguage is disabled or failed to make a good enough prediction.

    Definition Classes
    LanguageDetectionParams
  19. final def eq(arg0: AnyRef): Boolean

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

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

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    Definition Classes
    Params
  22. def explainParams(): String

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

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

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    Definition Classes
    Params
  25. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  26. 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
  27. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[SequenceModel[T, OPVector]]

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

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

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

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    Function that fits the sequence model

    Function that fits the sequence model

    Definition Classes
    SmartTextVectorizerSequenceEstimator
  31. final def get[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  32. def getAutoDetectLanguage: Boolean

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    Definition Classes
    LanguageDetectionParams
  33. def getAutoDetectThreshold: Double

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    Definition Classes
    LanguageDetectionParams
  34. final def getClass(): Class[_]

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

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    Definition Classes
    Params
  36. def getDefaultLanguage: Language

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    Definition Classes
    LanguageDetectionParams
  37. def getHashAlgorithm: HashAlgorithm

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    Definition Classes
    HashingVectorizerParams
  38. def getHashSpaceStrategy: HashSpaceStrategy

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    Definition Classes
    HashingVectorizerParams
  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 getMaxCardinality: Int

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

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    Definition Classes
    OpPipelineStageParams
  44. def getMinTokenLength: Int

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    Definition Classes
    TextTokenizerParams
  45. def getNumFeatures(): Int

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

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    Definition Classes
    Params
  47. 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
  48. 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
  49. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  50. def getToLowercase: Boolean

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    Definition Classes
    TextTokenizerParams
  51. 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
  52. final def getTransientFeatures(): Array[TransientFeature]

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    Gets the input Features

    Gets the input Features

    returns

    input features

    Definition Classes
    InputParams
  53. def getUnseenName: String

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

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

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    Definition Classes
    Params
  56. 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
  57. final val hashAlgorithm: Param[String]

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    Definition Classes
    HashingVectorizerParams
  58. def hashCode(): Int

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

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    Definition Classes
    HashingVectorizerParams
  60. final val hashWithIndex: BooleanParam

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    Definition Classes
    HashingVectorizerParams
  61. def hashingTF(params: HashingFunctionParams): HashingTF

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    HashingTF instance

    HashingTF instance

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  65. 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
  66. final def isDefined(param: Param[_]): Boolean

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

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

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    Definition Classes
    Params
  69. 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
  70. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  71. def log: Logger

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

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  78. def logName: String

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    OneHotFun
  84. def makeVectorColumnMetadata(features: Array[TransientFeature], params: HashingFunctionParams): Array[OpVectorColumnMetadata]

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

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

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    Attributes
    protected
    Definition Classes
    HashingFun
  87. final val maxCardinality: IntParam

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    Definition Classes
    MaxCardinalityParams
  88. final val minSupport: IntParam

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    Definition Classes
    MinSupportParam
  89. final val minTokenLength: IntParam

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    Minimum token length, >= 1.

    Minimum token length, >= 1.

    Definition Classes
    TextTokenizerParams
  90. final def ne(arg0: AnyRef): Boolean

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

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

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    Definition Classes
    AnyRef
  93. final val numFeatures: IntParam

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    Definition Classes
    HashingVectorizerParams
  94. def onGetMetadata(): Unit

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    Function to be called on getMetadata

    Function to be called on getMetadata

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

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    Function to be called on setInput

    Function to be called on setInput

    Attributes
    protected
    Definition Classes
    OpPipelineStageBase
  96. 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
  97. 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
  98. def outputFeatureUid: String

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    Attributes
    protected[com.salesforce.op]
    Definition Classes
    OpPipelineStageNOpPipelineStage
  99. 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
  100. lazy val params: Array[Param[_]]

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    Definition Classes
    Params
  101. 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
  102. final val prependFeatureName: BooleanParam

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

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

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

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

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

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

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    Definition Classes
    Params
  109. def setAutoDetectLanguage(value: Boolean): SmartTextVectorizer.this.type

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    Definition Classes
    LanguageDetectionParams
  110. def setAutoDetectThreshold(value: Double): SmartTextVectorizer.this.type

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    Definition Classes
    LanguageDetectionParams
  111. def setBinaryFreq(v: Boolean): SmartTextVectorizer.this.type

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    Definition Classes
    HashingVectorizerParams
  112. def setCleanText(clean: Boolean): SmartTextVectorizer.this.type

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

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

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    Attributes
    protected
    Definition Classes
    Params
  115. def setDefaultLanguage(value: Language): SmartTextVectorizer.this.type

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    Definition Classes
    LanguageDetectionParams
  116. def setHashAlgorithm(h: HashAlgorithm): SmartTextVectorizer.this.type

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    Definition Classes
    HashingVectorizerParams
  117. def setHashSpaceStrategy(v: HashSpaceStrategy): SmartTextVectorizer.this.type

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    Definition Classes
    HashingVectorizerParams
  118. def setHashWithIndex(v: Boolean): SmartTextVectorizer.this.type

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

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    Definition Classes
    OpPipelineStageN
  120. final def setInput(features: InputFeatures): SmartTextVectorizer.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
  121. final def setInputFeatures[S <: OPFeature](features: Array[S]): SmartTextVectorizer.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
  122. final def setMaxCardinality(v: Int): SmartTextVectorizer.this.type

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    Definition Classes
    MaxCardinalityParams
  123. final def setMetadata(m: Metadata): SmartTextVectorizer.this.type

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    Definition Classes
    OpPipelineStageParams
  124. def setMinSupport(min: Int): SmartTextVectorizer.this.type

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    Definition Classes
    MinSupportParam
  125. def setMinTokenLength(value: Int): SmartTextVectorizer.this.type

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    Definition Classes
    TextTokenizerParams
  126. def setNumFeatures(v: Int): SmartTextVectorizer.this.type

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    Definition Classes
    HashingVectorizerParams
  127. def setOutputFeatureName(name: String): SmartTextVectorizer.this.type

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    Definition Classes
    OpPipelineStage
  128. def setPrependFeatureName(v: Boolean): SmartTextVectorizer.this.type

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    Definition Classes
    HashingVectorizerParams
  129. def setToLowercase(value: Boolean): SmartTextVectorizer.this.type

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    Definition Classes
    TextTokenizerParams
  130. def setTopK(numberToKeep: Int): SmartTextVectorizer.this.type

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    Definition Classes
    PivotParams
  131. def setTrackNulls(v: Boolean): SmartTextVectorizer.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
  132. def setUnseenName(unseenNameIn: String): SmartTextVectorizer.this.type

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    Definition Classes
    SaveOthersParams
  133. 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
  134. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  135. final val toLowercase: BooleanParam

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    Indicates whether to convert all characters to lowercase before tokenizing.

    Indicates whether to convert all characters to lowercase before tokenizing.

    Definition Classes
    TextTokenizerParams
  136. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any
  137. def tokenize(text: Text, languageDetector: LanguageDetector = TextTokenizer.LanguageDetector, analyzer: TextAnalyzer = TextTokenizer.Analyzer): TextTokenizerResult

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    Definition Classes
    TextTokenizerParams
  138. final val topK: IntParam

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    Definition Classes
    PivotParams
  139. final val trackNulls: BooleanParam

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    Definition Classes
    TrackNullsParam
  140. 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
  141. def transformSchema(schema: StructType, logging: Boolean): StructType

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

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    type tag for input

    type tag for input

    Definition Classes
    SequenceEstimator
  143. 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
  144. implicit val tto: scala.reflect.api.JavaUniverse.TypeTag[OPVector]

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    type tag for input

    type tag for input

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

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    type tag for output value

    type tag for output value

    Definition Classes
    SequenceEstimatorOpPipelineStageN
  146. val uid: String

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    uid for instance

    uid for instance

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

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

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

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

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

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    Definition Classes
    OpPipelineStageBase → MLWritable

Inherited from MaxCardinalityParams

Inherited from OneHotFun

Inherited from HashingFun

Inherited from HashingVectorizerParams

Inherited from TextTokenizerParams

Inherited from LanguageDetectionParams

Inherited from MinSupportParam

Inherited from TrackNullsParam

Inherited from SaveOthersParams

Inherited from CleanTextFun

Inherited from PivotParams

Inherited from TextParams

Inherited from SequenceEstimator[T, OPVector]

Inherited from OpPipelineStageN[T, OPVector]

Inherited from HasInN

Inherited from OpPipelineStage[OPVector]

Inherited from OpPipelineStageBase

Inherited from MLWritable

Inherited from OpPipelineStageParams

Inherited from InputParams

Inherited from Estimator[SequenceModel[T, OPVector]]

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Ungrouped