Class/Object

com.salesforce.op.stages.impl.feature

NumericBucketizer

Related Docs: object NumericBucketizer | package feature

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class NumericBucketizer[I1 <: OPNumeric[_]] extends UnaryTransformer[I1, OPVector] with VectorizerDefaults with NumericBucketizerParams with NumericBucketizerMetadata

Numeric Bucketizer

I1

numeric feature type

Linear Supertypes
NumericBucketizerMetadata, NumericBucketizerParams, TrackNullsParam, TrackInvalidParam, VectorizerDefaults, UnaryTransformer[I1, OPVector], OpTransformer1[I1, OPVector], OpTransformer, OpPipelineStage1[I1, OPVector], HasIn1, OpPipelineStage[OPVector], OpPipelineStageBase, MLWritable, OpPipelineStageParams, InputParams, Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. NumericBucketizer
  2. NumericBucketizerMetadata
  3. NumericBucketizerParams
  4. TrackNullsParam
  5. TrackInvalidParam
  6. VectorizerDefaults
  7. UnaryTransformer
  8. OpTransformer1
  9. OpTransformer
  10. OpPipelineStage1
  11. HasIn1
  12. OpPipelineStage
  13. OpPipelineStageBase
  14. MLWritable
  15. OpPipelineStageParams
  16. InputParams
  17. Transformer
  18. PipelineStage
  19. Logging
  20. Params
  21. Serializable
  22. Serializable
  23. Identifiable
  24. AnyRef
  25. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new NumericBucketizer(operationName: String = "numBuck", uid: String = UID[NumericBucketizer[_]])(implicit tti1: scala.reflect.api.JavaUniverse.TypeTag[I1])

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    operationName

    unique name of the operation this stage performs

    uid

    uid for instance

    tti1

    type tag for numeric feature type

Type Members

  1. final type InputFeatures = FeatureLike[I1]

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    Input Features type

    Input Features type

    Definition Classes
    OpPipelineStage1OpPipelineStageInputParams
  2. type KeyValue = (String) ⇒ Any

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

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

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

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    Definition Classes
    OpPipelineStageOpPipelineStageBase

Value Members

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

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

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

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

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

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    Definition Classes
    Any
  6. implicit def booleanToDouble(v: Boolean): Double

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    Definition Classes
    VectorizerDefaults
  7. final val bucketLabels: StringArrayParam

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    Definition Classes
    NumericBucketizerParams
  8. final def checkInputLength(features: Array[_]): Boolean

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    Checks the input length

    Checks the input length

    features

    input features

    returns

    true is input size as expected, false otherwise

    Definition Classes
    OpPipelineStage1InputParams
  9. final def checkSerializable: Try[Unit]

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    Check if the stage is serializable

    Check if the stage is serializable

    returns

    Failure if not serializable

    Definition Classes
    OpTransformer1OpPipelineStageBase
  10. final def clear(param: Param[_]): NumericBucketizer.this.type

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    Definition Classes
    Params
  11. def clone(): AnyRef

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

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

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

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

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

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    Definition Classes
    Params
  18. def explainParams(): String

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

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

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    Definition Classes
    Params
  21. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  22. final def get[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  23. def getBucketLabels: Array[String]

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    Definition Classes
    NumericBucketizerParams
  24. final def getClass(): Class[_]

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

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    Definition Classes
    Params
  26. 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

  27. 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

  28. final def getInputSchema(): StructType

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    Definition Classes
    OpPipelineStageParams
  29. final def getMetadata(): Metadata

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

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    Definition Classes
    Params
  31. 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
    OpPipelineStage1OpPipelineStageBase
  32. 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
  33. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  34. def getSplitInclusion: Inclusion

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    Definition Classes
    NumericBucketizerParams
  35. def getSplits: Array[Double]

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    Definition Classes
    NumericBucketizerParams
  36. 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
  37. final def getTransientFeatures(): Array[TransientFeature]

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    Gets the input Features

    Gets the input Features

    returns

    input features

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

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

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    Definition Classes
    Params
  40. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  41. final def in1: TransientFeature

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  44. 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
    OpPipelineStage1InputParams
  45. final def isDefined(param: Param[_]): Boolean

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

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

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    Definition Classes
    Params
  48. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  49. def log: Logger

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

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  56. def logName: String

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  61. def makeVectorColumnMetadata(input: TransientFeature, bucketLabels: Array[String], grouping: Option[String], trackInvalid: Boolean, trackNulls: Boolean): Array[OpVectorColumnMetadata]

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    Attributes
    protected
    Definition Classes
    NumericBucketizerMetadata
  62. def makeVectorMetadata(input: TransientFeature, bucketLabels: Array[String], trackInvalid: Boolean, trackNulls: Boolean): OpVectorMetadata

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    Attributes
    protected
    Definition Classes
    NumericBucketizerMetadata
  63. final def ne(arg0: AnyRef): Boolean

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

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

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    Definition Classes
    AnyRef
  66. def onGetMetadata(): Unit

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    Function to be called on getMetadata

    Function to be called on getMetadata

    Definition Classes
    NumericBucketizerOpPipelineStageParams
  67. def onSetInput(): Unit

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    Function to be called on setInput

    Function to be called on setInput

    Definition Classes
    VectorizerDefaultsOpPipelineStageBase
  68. 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
    UnaryTransformerOpPipelineStageBase
  69. 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
  70. def outputFeatureUid: String

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    Attributes
    protected[com.salesforce.op]
    Definition Classes
    OpPipelineStage1OpPipelineStage
  71. 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
  72. 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
  73. lazy val params: Array[Param[_]]

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

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

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

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

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    Definition Classes
    Params
  78. def setBuckets(splits: Array[Double], bucketLabels: Option[Array[String]] = None): NumericBucketizer.this.type

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    Sets the points for bucketizing

    Sets the points for bucketizing

    splits

    sorted list of split points for bucketizing

    bucketLabels

    optional sorted list of labels for the buckets

    Definition Classes
    NumericBucketizerParams
  79. final def setDefault(paramPairs: ParamPair[_]*): NumericBucketizer.this.type

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

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    Attributes
    protected
    Definition Classes
    Params
  81. final def setInput(features: InputFeatures): NumericBucketizer.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
  82. final def setInputFeatures[S <: OPFeature](features: Array[S]): NumericBucketizer.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
  83. final def setMetadata(m: Metadata): NumericBucketizer.this.type

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    Definition Classes
    OpPipelineStageParams
  84. def setOutputFeatureName(name: String): NumericBucketizer.this.type

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    Definition Classes
    OpPipelineStage
  85. def setSplitInclusion(v: Inclusion): NumericBucketizer.this.type

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    Should the splits be left or right inclusive.

    Should the splits be left or right inclusive. Meaning if x1 and x2 are split points, then for Left the bucket interval is [x1, x2) and for Right the bucket interval is (x1, x2].

    Definition Classes
    NumericBucketizerParams
  86. def setTrackInvalid(v: Boolean): NumericBucketizer.this.type

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    Option to keep track of invalid values

    Option to keep track of invalid values

    Definition Classes
    TrackInvalidParam
  87. def setTrackNulls(v: Boolean): NumericBucketizer.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
  88. final val splitInclusion: Param[String]

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    Definition Classes
    NumericBucketizerParams
  89. final val splits: DoubleArrayParam

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    Definition Classes
    NumericBucketizerParams
  90. 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
  91. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  92. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any
  93. final val trackInvalid: BooleanParam

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    Definition Classes
    TrackInvalidParam
  94. final val trackNulls: BooleanParam

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    Definition Classes
    TrackNullsParam
  95. def transform(dataset: Dataset[_]): DataFrame

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

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

    dataset

    input data for this stage

    returns

    a new dataset containing a column for the transformed feature

    Definition Classes
    OpTransformer1 → Transformer
  96. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

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

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  98. def transformFn: (I1) ⇒ OPVector

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    Function used to convert input to output

    Function used to convert input to output

    Definition Classes
    NumericBucketizerOpTransformer1
  99. lazy val transformKeyValue: (KeyValue) ⇒ Any

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

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

    returns

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

    Definition Classes
    OpTransformer1 → OpTransformer
  100. def transformMap: (Map[String, Any]) ⇒ Any

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    Creates a transform function to transform Map to a value

    Creates a transform function to transform Map to a value

    returns

    a transform function to transform Map to a value

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

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    Creates a transform function to transform Row to a value

    Creates a transform function to transform Row to a value

    returns

    a transform function to transform Row to a value

    Definition Classes
    OpTransformer
  102. 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
  103. def transformSchema(schema: StructType, logging: Boolean): StructType

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  104. implicit val tti: scala.reflect.api.JavaUniverse.TypeTag[I1]

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    type tag for input

    type tag for input

    Definition Classes
    UnaryTransformerOpTransformer1
  105. implicit val tti1: scala.reflect.api.JavaUniverse.TypeTag[I1]

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    type tag for numeric feature type

  106. implicit val tto: scala.reflect.api.JavaUniverse.TypeTag[OPVector]

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    type tag for output

    type tag for output

    Definition Classes
    UnaryTransformerOpPipelineStage1
  107. 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
    UnaryTransformerOpPipelineStage1
  108. val uid: String

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    uid for instance

    uid for instance

    Definition Classes
    UnaryTransformer → Identifiable
  109. 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
  110. def vectorMetadataWithNullIndicators: OpVectorMetadata

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    Attributes
    protected
    Definition Classes
    VectorizerDefaults
  111. 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
  112. final def wait(): Unit

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

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

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

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    Definition Classes
    OpPipelineStageBase → MLWritable

Inherited from NumericBucketizerMetadata

Inherited from NumericBucketizerParams

Inherited from TrackNullsParam

Inherited from TrackInvalidParam

Inherited from VectorizerDefaults

Inherited from UnaryTransformer[I1, OPVector]

Inherited from OpTransformer1[I1, OPVector]

Inherited from OpTransformer

Inherited from OpPipelineStage1[I1, OPVector]

Inherited from HasIn1

Inherited from OpPipelineStage[OPVector]

Inherited from OpPipelineStageBase

Inherited from MLWritable

Inherited from OpPipelineStageParams

Inherited from InputParams

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Ungrouped