Class

com.salesforce.op.stages.impl.feature

SmartTextMapVectorizer

Related Doc: package feature

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class SmartTextMapVectorizer[T <: OPMap[String]] extends SequenceEstimator[T, OPVector] with PivotParams with CleanTextFun with SaveOthersParams with TrackNullsParam with MinSupportParam with TextTokenizerParams with HashingVectorizerParams with MapHashingFun with OneHotFun with MapStringPivotHelper with MapVectorizerFuns[String, OPMap[String]] with MaxCardinalityParams

Convert a sequence of text map 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).

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Inherited
  1. SmartTextMapVectorizer
  2. MaxCardinalityParams
  3. MapVectorizerFuns
  4. CleanTextMapFun
  5. MapPivotParams
  6. VectorizerDefaults
  7. MapStringPivotHelper
  8. OneHotFun
  9. MapHashingFun
  10. HashingFun
  11. HashingVectorizerParams
  12. TextTokenizerParams
  13. LanguageDetectionParams
  14. MinSupportParam
  15. TrackNullsParam
  16. SaveOthersParams
  17. CleanTextFun
  18. PivotParams
  19. TextParams
  20. SequenceEstimator
  21. OpPipelineStageN
  22. HasInN
  23. OpPipelineStage
  24. OpPipelineStageBase
  25. MLWritable
  26. OpPipelineStageParams
  27. InputParams
  28. Estimator
  29. PipelineStage
  30. Logging
  31. Params
  32. Serializable
  33. Serializable
  34. Identifiable
  35. AnyRef
  36. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new SmartTextMapVectorizer(uid: String = UID[SmartTextMapVectorizer[T]])(implicit tti: scala.reflect.api.JavaUniverse.TypeTag[T], ttiv: scala.reflect.api.JavaUniverse.TypeTag[Map[String, String]])

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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. type MapMap = Map[String, Map[String, Long]]

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    Definition Classes
    MapStringPivotHelper
  3. final type OutputFeatures = FeatureLike[OPVector]

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    Definition Classes
    OpPipelineStageOpPipelineStageBase
  4. type SeqMapMap = Seq[utils.spark.SequenceAggregators.MapMap]

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    Definition Classes
    MapStringPivotHelper
  5. type SeqSeqTupArr = Seq[Seq[(String, Array[String])]]

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    Definition Classes
    MapStringPivotHelper

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 val blackListKeys: StringArrayParam

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    Definition Classes
    MapPivotParams
  10. implicit def booleanToDouble(v: Boolean): Double

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    Definition Classes
    VectorizerDefaults
  11. 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
  12. 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
  13. final val cleanKeys: BooleanParam

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    Definition Classes
    MapPivotParams
  14. def cleanMap[V](m: Map[String, V], shouldCleanKey: Boolean, shouldCleanValue: Boolean): Map[String, V]

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    Definition Classes
    CleanTextMapFun
  15. final val cleanText: BooleanParam

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

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

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    Definition Classes
    Params
  18. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  19. final def copy(extra: ParamMap): SmartTextMapVectorizer.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
  20. def copyValues[T <: Params](to: T, extra: ParamMap): T

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

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    Attributes
    protected
    Definition Classes
    Params
  22. 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
  23. final def eq(arg0: AnyRef): Boolean

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

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

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    Definition Classes
    Params
  26. def explainParams(): String

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

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

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    Definition Classes
    Params
  29. def filterKeys[V](m: Map[String, V], shouldCleanKey: Boolean, shouldCleanValue: Boolean): Map[String, V]

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    Attributes
    protected
    Definition Classes
    MapPivotParams
  30. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  31. 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
  32. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[SequenceModel[T, OPVector]]

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

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

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

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    Function that fits the sequence model

    Function that fits the sequence model

    Definition Classes
    SmartTextMapVectorizerSequenceEstimator
  36. final def get[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  37. def getAutoDetectLanguage: Boolean

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    Definition Classes
    LanguageDetectionParams
  38. def getAutoDetectThreshold: Double

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    Definition Classes
    LanguageDetectionParams
  39. def getCategoryMaps[V](in: Dataset[Seq[Map[String, V]]], convertToMapOfMaps: (Map[String, V]) ⇒ MapMap, shouldCleanKeys: Boolean, shouldCleanValues: Boolean): Dataset[SeqMapMap]

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    Attributes
    protected
    Definition Classes
    MapStringPivotHelper
  40. final def getClass(): Class[_]

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

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    Definition Classes
    Params
  42. def getDefaultLanguage: Language

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    Definition Classes
    LanguageDetectionParams
  43. def getHashAlgorithm: HashAlgorithm

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    Definition Classes
    HashingVectorizerParams
  44. def getHashSpaceStrategy: HashSpaceStrategy

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    Definition Classes
    HashingVectorizerParams
  45. 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

  46. 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

  47. final def getInputSchema(): StructType

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    Definition Classes
    OpPipelineStageParams
  48. def getKeyValues(in: Dataset[Seq[Map[String, String]]], shouldCleanKeys: Boolean, shouldCleanValues: Boolean): Seq[Seq[String]]

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    Attributes
    protected
    Definition Classes
    MapVectorizerFuns
  49. final def getMaxCardinality: Int

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

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    Definition Classes
    OpPipelineStageParams
  51. def getMinTokenLength: Int

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    Definition Classes
    TextTokenizerParams
  52. def getNumFeatures(): Int

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

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    Definition Classes
    Params
  54. 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
  55. 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
  56. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  57. def getToLowercase: Boolean

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    Definition Classes
    TextTokenizerParams
  58. def getTopValues(categoryMaps: Dataset[SeqMapMap], inputSize: Int, topK: Int, minSup: Int): SeqSeqTupArr

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    Attributes
    protected
    Definition Classes
    MapStringPivotHelper
  59. 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
  60. final def getTransientFeatures(): Array[TransientFeature]

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    Gets the input Features

    Gets the input Features

    returns

    input features

    Definition Classes
    InputParams
  61. def getUnseenName: String

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

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

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    Definition Classes
    Params
  64. def hash(inputs: Seq[Map[String, TextList]], allKeys: Seq[Seq[String]], params: HashingFunctionParams): OPVector

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    Attributes
    protected
    Definition Classes
    MapHashingFun
  65. 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
  66. final val hashAlgorithm: Param[String]

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    Definition Classes
    HashingVectorizerParams
  67. def hashCode(): Int

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

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    Definition Classes
    HashingVectorizerParams
  69. final val hashWithIndex: BooleanParam

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

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    HashingTF instance

    HashingTF instance

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  74. 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
  75. final def isDefined(param: Param[_]): Boolean

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

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

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    Definition Classes
    Params
  78. 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
  79. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  80. def log: Logger

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

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  87. def logName: String

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  92. def makeOutputVectorMetadata(topValues: SeqSeqTupArr, inputFeatures: Array[TransientFeature], operationName: String, outputName: String, stageName: String, trackNulls: Boolean = false): OpVectorMetadata

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    Attributes
    protected
    Definition Classes
    MapStringPivotHelper
  93. def makeSmartTextMapVectorizerModelArgs(aggregatedStats: Array[TextMapStats]): SmartTextMapVectorizerModelArgs

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  94. def makeVectorColumnMetadata(topValues: SeqSeqTupArr, inputFeatures: Array[TransientFeature], unseenName: String, trackNulls: Boolean = false): Array[OpVectorColumnMetadata]

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    Attributes
    protected
    Definition Classes
    MapStringPivotHelper
  95. 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
  96. def makeVectorColumnMetadata(features: Array[TransientFeature], params: HashingFunctionParams, allKeys: Seq[Seq[String]], shouldTrackNulls: Boolean): Array[OpVectorColumnMetadata]

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

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    Attributes
    protected
    Definition Classes
    HashingFun
  98. def makeVectorMetaWithNullIndicators(allKeys: Seq[Seq[String]]): OpVectorMetadata

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    Attributes
    protected
    Definition Classes
    MapVectorizerFuns
  99. def makeVectorMetadata(allKeys: Seq[Seq[String]]): OpVectorMetadata

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    Attributes
    protected
    Definition Classes
    MapVectorizerFuns
  100. 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
  101. def makeVectorMetadata(features: Array[TransientFeature], params: HashingFunctionParams, outputName: String): OpVectorMetadata

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

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    Definition Classes
    MaxCardinalityParams
  103. final val minSupport: IntParam

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    Definition Classes
    MinSupportParam
  104. final val minTokenLength: IntParam

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    Minimum token length, >= 1.

    Minimum token length, >= 1.

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

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

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

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    Definition Classes
    AnyRef
  108. final val numFeatures: IntParam

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    Definition Classes
    HashingVectorizerParams
  109. def onGetMetadata(): Unit

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    Function to be called on getMetadata

    Function to be called on getMetadata

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

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    Function to be called on setInput

    Function to be called on setInput

    Definition Classes
    VectorizerDefaultsOpPipelineStageBase
  111. 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
  112. 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
  113. def outputFeatureUid: String

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    Attributes
    protected[com.salesforce.op]
    Definition Classes
    OpPipelineStageNOpPipelineStage
  114. 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
  115. def outputVectorMeta: OpVectorMetadata

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    Get the metadata describing the output vector

    Get the metadata describing the output vector

    This does not trigger onGetMetadata()

    returns

    Metadata of output vector

    Attributes
    protected
    Definition Classes
    VectorizerDefaults
  116. lazy val params: Array[Param[_]]

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    Definition Classes
    Params
  117. 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
  118. final val prependFeatureName: BooleanParam

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

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

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

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    Definition Classes
    SequenceEstimator
  122. implicit val seqMapEncoder: Encoder[Seq[Map[String, String]]]

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    Attributes
    protected
    Definition Classes
    MapStringPivotHelper
  123. implicit val seqMapMapEncoder: Encoder[SeqMapMap]

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    Attributes
    protected
    Definition Classes
    MapStringPivotHelper
  124. implicit val seqSeqArrayEncoder: Encoder[SeqSeqTupArr]

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    Attributes
    protected
    Definition Classes
    MapStringPivotHelper
  125. final def set(paramPair: ParamPair[_]): SmartTextMapVectorizer.this.type

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

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

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    Definition Classes
    Params
  128. def setAutoDetectLanguage(value: Boolean): SmartTextMapVectorizer.this.type

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    Definition Classes
    LanguageDetectionParams
  129. def setAutoDetectThreshold(value: Double): SmartTextMapVectorizer.this.type

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    Definition Classes
    LanguageDetectionParams
  130. def setBinaryFreq(v: Boolean): SmartTextMapVectorizer.this.type

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    Definition Classes
    HashingVectorizerParams
  131. final def setBlackListKeys(keys: Array[String]): SmartTextMapVectorizer.this.type

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    Definition Classes
    MapPivotParams
  132. def setCleanKeys(clean: Boolean): SmartTextMapVectorizer.this.type

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    Definition Classes
    MapPivotParams
  133. def setCleanText(clean: Boolean): SmartTextMapVectorizer.this.type

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

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

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    Attributes
    protected
    Definition Classes
    Params
  136. def setDefaultLanguage(value: Language): SmartTextMapVectorizer.this.type

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    Definition Classes
    LanguageDetectionParams
  137. def setHashAlgorithm(h: HashAlgorithm): SmartTextMapVectorizer.this.type

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    Definition Classes
    HashingVectorizerParams
  138. def setHashSpaceStrategy(v: HashSpaceStrategy): SmartTextMapVectorizer.this.type

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    Definition Classes
    HashingVectorizerParams
  139. def setHashWithIndex(v: Boolean): SmartTextMapVectorizer.this.type

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

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    Definition Classes
    OpPipelineStageN
  141. final def setInput(features: InputFeatures): SmartTextMapVectorizer.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
  142. final def setInputFeatures[S <: OPFeature](features: Array[S]): SmartTextMapVectorizer.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
  143. final def setMaxCardinality(v: Int): SmartTextMapVectorizer.this.type

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    Definition Classes
    MaxCardinalityParams
  144. final def setMetadata(m: Metadata): SmartTextMapVectorizer.this.type

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    Definition Classes
    OpPipelineStageParams
  145. def setMinSupport(min: Int): SmartTextMapVectorizer.this.type

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    Definition Classes
    MinSupportParam
  146. def setMinTokenLength(value: Int): SmartTextMapVectorizer.this.type

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    Definition Classes
    TextTokenizerParams
  147. def setNumFeatures(v: Int): SmartTextMapVectorizer.this.type

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    Definition Classes
    HashingVectorizerParams
  148. def setOutputFeatureName(name: String): SmartTextMapVectorizer.this.type

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    Definition Classes
    OpPipelineStage
  149. def setPrependFeatureName(v: Boolean): SmartTextMapVectorizer.this.type

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    Definition Classes
    HashingVectorizerParams
  150. def setToLowercase(value: Boolean): SmartTextMapVectorizer.this.type

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    Definition Classes
    TextTokenizerParams
  151. def setTopK(numberToKeep: Int): SmartTextMapVectorizer.this.type

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    Definition Classes
    PivotParams
  152. def setTrackNulls(v: Boolean): SmartTextMapVectorizer.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
  153. def setUnseenName(unseenNameIn: String): SmartTextMapVectorizer.this.type

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    Definition Classes
    SaveOthersParams
  154. final def setWhiteListKeys(keys: Array[String]): SmartTextMapVectorizer.this.type

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    Definition Classes
    MapPivotParams
  155. 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
  156. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  157. 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
  158. def toString(): String

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

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    Definition Classes
    TextTokenizerParams
  160. final val topK: IntParam

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    Definition Classes
    PivotParams
  161. final val trackNulls: BooleanParam

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    Definition Classes
    TrackNullsParam
  162. 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
  163. def transformSchema(schema: StructType, logging: Boolean): StructType

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

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    type tag for input

    type tag for input

    Definition Classes
    SequenceEstimator
  165. 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
  166. implicit val tto: scala.reflect.api.JavaUniverse.TypeTag[OPVector]

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    type tag for input

    type tag for input

    Definition Classes
    SequenceEstimatorOpPipelineStageN
  167. 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
  168. val uid: String

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    uid for instance

    uid for instance

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

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    Definition Classes
    SaveOthersParams
  170. def vectorMetadataFromInputFeatures: OpVectorMetadata

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    Compute the output vector metadata only from the input features.

    Compute the output vector metadata only from the input features. Vectorizers use this to derive the full vector, including pivot columns or indicator features.

    returns

    Vector metadata from input features

    Attributes
    protected
    Definition Classes
    VectorizerDefaults
  171. def vectorMetadataWithNullIndicators: OpVectorMetadata

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    Attributes
    protected
    Definition Classes
    VectorizerDefaults
  172. def vectorOutputName: String

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    Get the name of the output vector

    Get the name of the output vector

    returns

    Output vector name as a string

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

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

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  176. final val whiteListKeys: StringArrayParam

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    Definition Classes
    MapPivotParams
  177. final def write: MLWriter

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    Definition Classes
    OpPipelineStageBase → MLWritable

Inherited from MaxCardinalityParams

Inherited from MapVectorizerFuns[String, OPMap[String]]

Inherited from CleanTextMapFun

Inherited from MapPivotParams

Inherited from VectorizerDefaults

Inherited from MapStringPivotHelper

Inherited from OneHotFun

Inherited from MapHashingFun

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