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 TrackTextLenParam 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, UniqueCountFun, HashingFun, HashingVectorizerParams, TrackTextLenParam, TextTokenizerParams, TextMatchingParams, LanguageDetectionParams, MinSupportParam, TrackNullsParam, SaveOthersParams, CleanTextFun, PivotParams, TextParams, SequenceEstimator[T, OPVector], OpPipelineStageN[T, OPVector], HasOut[OPVector], HasInN, OpPipelineStage[OPVector], OpPipelineStageBase, MLWritable, OpPipelineStageParams, InputParams, Estimator[SequenceModel[T, OPVector]], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. SmartTextVectorizer
  2. MaxCardinalityParams
  3. OneHotFun
  4. UniqueCountFun
  5. HashingFun
  6. HashingVectorizerParams
  7. TrackTextLenParam
  8. TextTokenizerParams
  9. TextMatchingParams
  10. LanguageDetectionParams
  11. MinSupportParam
  12. TrackNullsParam
  13. SaveOthersParams
  14. CleanTextFun
  15. PivotParams
  16. TextParams
  17. SequenceEstimator
  18. OpPipelineStageN
  19. HasOut
  20. HasInN
  21. OpPipelineStage
  22. OpPipelineStageBase
  23. MLWritable
  24. OpPipelineStageParams
  25. InputParams
  26. Estimator
  27. PipelineStage
  28. Logging
  29. Params
  30. Serializable
  31. Serializable
  32. Identifiable
  33. AnyRef
  34. 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. def countMapUniques[V](dataset: Dataset[Seq[Map[String, V]]], size: Int, bits: Int)(implicit kryo: KryoSerializer, ct: ClassTag[V]): (Seq[Map[String, HLL]], Long)

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

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

    V

    value type

    dataset

    dataset to count unique values

    size

    size of each sequence component

    bits

    number of bits for HyperLogLog HLL

    kryo

    kryo serializer to serialize V value into array of bytes

    ct

    class tag of V - needed by kryo

    returns

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

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

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

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

    V

    value type

    dataset

    dataset to count unique values

    size

    size of each sequence component

    bits

    number of bits for HyperLogLog HLL

    kryo

    kryo serializer to serialize V value into array of bytes

    ct

    class tag of V - needed by kryo

    returns

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

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

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

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

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

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    Definition Classes
    Params
  24. def explainParams(): String

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

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

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    Definition Classes
    Params
  27. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  28. 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
  29. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[SequenceModel[T, OPVector]]

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

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

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  32. 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
  33. final def get[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  34. def getAutoDetectLanguage: Boolean

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    Definition Classes
    LanguageDetectionParams
  35. def getAutoDetectThreshold: Double

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

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

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    Definition Classes
    Params
  38. def getDefaultLanguage: Language

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    Definition Classes
    LanguageDetectionParams
  39. def getHashAlgorithm: HashAlgorithm

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    Definition Classes
    HashingVectorizerParams
  40. def getHashSpaceStrategy: HashSpaceStrategy

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    Definition Classes
    HashingVectorizerParams
  41. 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

  42. 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

  43. final def getInputSchema(): StructType

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    Definition Classes
    OpPipelineStageParams
  44. final def getMaxCardinality: Int

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

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    Definition Classes
    OpPipelineStageParams
  46. def getMinTokenLength: Int

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    Definition Classes
    TextTokenizerParams
  47. def getNumFeatures(): Int

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

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

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    Definition Classes
    HasOut
  50. 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
  51. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  52. def getToLowercase: Boolean

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    Definition Classes
    TextMatchingParams
  53. 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
  54. final def getTransientFeatures(): Array[TransientFeature]

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    Gets the input Features

    Gets the input Features

    returns

    input features

    Definition Classes
    InputParams
  55. def getUnseenName: String

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

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

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    Definition Classes
    Params
  58. 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
  59. final val hashAlgorithm: Param[String]

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    Definition Classes
    HashingVectorizerParams
  60. def hashCode(): Int

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

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    Definition Classes
    HashingVectorizerParams
  62. final val hashWithIndex: BooleanParam

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

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    HashingTF instance

    HashingTF instance

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  67. 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
  68. final def isDefined(param: Param[_]): Boolean

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

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

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    Definition Classes
    Params
  71. 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
  72. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  73. def log: Logger

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

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  80. def logName: String

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  85. 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
  86. def makeVectorColumnMetadata(features: Array[TransientFeature], params: HashingFunctionParams): Array[OpVectorColumnMetadata]

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    Attributes
    protected
    Definition Classes
    HashingFun
  87. 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
  88. def makeVectorMetadata(features: Array[TransientFeature], params: HashingFunctionParams, outputName: String): OpVectorMetadata

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

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    Definition Classes
    MaxCardinalityParams
  90. final val minSupport: IntParam

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    Definition Classes
    MinSupportParam
  91. final val minTokenLength: IntParam

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    Minimum token length, >= 1.

    Minimum token length, >= 1.

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

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

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

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    Definition Classes
    AnyRef
  95. final val numFeatures: IntParam

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    Definition Classes
    HashingVectorizerParams
  96. def onGetMetadata(): Unit

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    Function to be called on getMetadata

    Function to be called on getMetadata

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

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    Function to be called on setInput

    Function to be called on setInput

    Attributes
    protected
    Definition Classes
    InputParams
  98. 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
  99. 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
  100. def outputFeatureUid: String

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    Attributes
    protected[com.salesforce.op]
    Definition Classes
    OpPipelineStageNOpPipelineStage
  101. 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
  102. lazy val params: Array[Param[_]]

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    Definition Classes
    Params
  103. 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
  104. final val prependFeatureName: BooleanParam

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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    Definition Classes
    OpPipelineStageN
  122. 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
  123. 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
  124. final def setMaxCardinality(v: Int): SmartTextVectorizer.this.type

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

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

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

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

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

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

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

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    Definition Classes
    TextMatchingParams
  132. def setTopK(numberToKeep: Int): SmartTextVectorizer.this.type

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    Definition Classes
    PivotParams
  133. 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
  134. def setTrackTextLen(v: Boolean): SmartTextVectorizer.this.type

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    Option to keep track of text lengths

    Option to keep track of text lengths

    Definition Classes
    TrackTextLenParam
  135. def setUnseenName(unseenNameIn: String): SmartTextVectorizer.this.type

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    Definition Classes
    SaveOthersParams
  136. 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
  137. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  138. final val toLowercase: BooleanParam

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    Indicates whether to convert all characters to lowercase before string operation.

    Indicates whether to convert all characters to lowercase before string operation.

    Definition Classes
    TextMatchingParams
  139. def toString(): String

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

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    Definition Classes
    TextTokenizerParams
  141. final val topK: IntParam

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    Definition Classes
    PivotParams
  142. final val trackNulls: BooleanParam

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    Definition Classes
    TrackNullsParam
  143. final val trackTextLen: BooleanParam

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    Definition Classes
    TrackTextLenParam
  144. 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
  145. def transformSchema(schema: StructType, logging: Boolean): StructType

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

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    type tag for input

    type tag for input

    Definition Classes
    SequenceEstimator
  147. 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
  148. implicit val tto: scala.reflect.api.JavaUniverse.TypeTag[OPVector]

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    type tag for input

    type tag for input

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

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    type tag for output value

    type tag for output value

    Definition Classes
    SequenceEstimator → HasOut
  150. val uid: String

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    uid for instance

    uid for instance

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

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

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

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

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

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    Definition Classes
    OpPipelineStageBase → MLWritable

Inherited from MaxCardinalityParams

Inherited from OneHotFun

Inherited from UniqueCountFun

Inherited from HashingFun

Inherited from HashingVectorizerParams

Inherited from TrackTextLenParam

Inherited from TextTokenizerParams

Inherited from TextMatchingParams

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 HasOut[OPVector]

Inherited from HasInN

Inherited from OpPipelineStage[OPVector]

Inherited from OpPipelineStageBase

Inherited from MLWritable

Inherited from OpPipelineStageParams

Inherited from InputParams

Inherited from Estimator[SequenceModel[T, OPVector]]

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Ungrouped