Class/Object

com.salesforce.op.stages.impl.feature

DecisionTreeNumericBucketizer

Related Docs: object DecisionTreeNumericBucketizer | package feature

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class DecisionTreeNumericBucketizer[N, I2 <: OPNumeric[N]] extends BinaryEstimator[RealNN, I2, OPVector] with DecisionTreeNumericBucketizerParams with VectorizerDefaults with TrackInvalidParam with TrackNullsParam with NumericBucketizerMetadata with AllowLabelAsInput[OPVector]

Smart bucketizer for numeric values based on a Decision Tree classifier.

N

numeric feature type value

I2

numeric feature type

Linear Supertypes
AllowLabelAsInput[OPVector], NumericBucketizerMetadata, TrackNullsParam, TrackInvalidParam, VectorizerDefaults, DecisionTreeNumericBucketizerParams, BinaryEstimator[RealNN, I2, OPVector], OpPipelineStage2[RealNN, I2, OPVector], HasOut[OPVector], HasIn2, HasIn1, OpPipelineStage[OPVector], OpPipelineStageBase, MLWritable, OpPipelineStageParams, InputParams, Estimator[BinaryModel[RealNN, I2, OPVector]], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. DecisionTreeNumericBucketizer
  2. AllowLabelAsInput
  3. NumericBucketizerMetadata
  4. TrackNullsParam
  5. TrackInvalidParam
  6. VectorizerDefaults
  7. DecisionTreeNumericBucketizerParams
  8. BinaryEstimator
  9. OpPipelineStage2
  10. HasOut
  11. HasIn2
  12. HasIn1
  13. OpPipelineStage
  14. OpPipelineStageBase
  15. MLWritable
  16. OpPipelineStageParams
  17. InputParams
  18. Estimator
  19. PipelineStage
  20. Logging
  21. Params
  22. Serializable
  23. Serializable
  24. Identifiable
  25. AnyRef
  26. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new DecisionTreeNumericBucketizer(operationName: String = "dtNumBuck", uid: String = ...)(implicit tti2: scala.reflect.api.JavaUniverse.TypeTag[I2], ttiv2: scala.reflect.api.JavaUniverse.TypeTag[Option[N]], nev: Numeric[N])

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    operationName

    unique name of the operation this stage performs

    uid

    uid for instance

    tti2

    type tag for numeric feature type

    ttiv2

    type tag for numeric feature value type

    nev

    numeric evidence for feature type value

Type Members

  1. final type InputFeatures = (FeatureLike[RealNN], FeatureLike[I2])

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    Definition Classes
    OpPipelineStage2 → OpPipelineStage → InputParams
  2. final type OutputFeatures = FeatureLike[OPVector]

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    Definition Classes
    OpPipelineStage → OpPipelineStageBase
  3. case class Splits(shouldSplit: Boolean, splits: Array[Double], bucketLabels: Array[String]) extends Product with Serializable

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    Computed splits

    Computed splits

    shouldSplit

    should or not split

    splits

    computed split values

    bucketLabels

    bucket labels

    Definition Classes
    DecisionTreeNumericBucketizerParams

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 def checkInputLength(features: Array[_]): Boolean

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    Definition Classes
    OpPipelineStage2 → InputParams
  8. final def checkSerializable: Try[Unit]

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    Definition Classes
    BinaryEstimator → OpPipelineStageBase
  9. final def clear(param: Param[_]): DecisionTreeNumericBucketizer.this.type

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    Definition Classes
    Params
  10. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  11. def computeSplits(data: Dataset[(Double, Double)], featureName: String): Splits

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    Compute splits using DecisionTreeClassifier

    Compute splits using DecisionTreeClassifier

    data

    input dataset of (label, feature) tuples

    featureName

    feature name

    returns

    computed Splits

    Attributes
    protected
    Definition Classes
    DecisionTreeNumericBucketizerParams
  12. val convertI1: FeatureTypeSparkConverter[RealNN]

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    Definition Classes
    BinaryEstimator
  13. val convertI2: FeatureTypeSparkConverter[I2]

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    Definition Classes
    BinaryEstimator
  14. final def copy(extra: ParamMap): DecisionTreeNumericBucketizer.this.type

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    Definition Classes
    OpPipelineStageBase → Params
  15. def copyValues[T <: Params](to: T, extra: ParamMap): T

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

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

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

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

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    Definition Classes
    Params
  20. def explainParams(): String

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

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

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    Definition Classes
    Params
  23. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  24. def fit(dataset: Dataset[_]): BinaryModel[RealNN, I2, OPVector]

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    Definition Classes
    BinaryEstimator → Estimator
  25. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[BinaryModel[RealNN, I2, OPVector]]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  26. def fit(dataset: Dataset[_], paramMap: ParamMap): BinaryModel[RealNN, I2, OPVector]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  27. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): BinaryModel[RealNN, I2, OPVector]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  28. def fitFn(dataset: Dataset[(Option[Double], Option[N])]): BinaryModel[RealNN, I2, OPVector]

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    Definition Classes
    DecisionTreeNumericBucketizer → BinaryEstimator
  29. final def get[T](param: Param[T]): Option[T]

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

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

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    Definition Classes
    Params
  32. final def getImpurity: String

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

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    Definition Classes
    InputParams
  34. final def getInputFeatures(): Array[OPFeature]

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    Definition Classes
    InputParams
  35. final def getInputSchema(): StructType

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    Definition Classes
    OpPipelineStageParams
  36. final def getMaxBins: Int

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  37. final def getMaxDepth: Int

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  38. final def getMetadata(): Metadata

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    Definition Classes
    OpPipelineStageParams
  39. final def getMinInfoGain: Double

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  40. final def getMinInstancesPerNode: Int

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  41. final def getOrDefault[T](param: Param[T]): T

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

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    Definition Classes
    HasOut → OpPipelineStageBase
  43. final def getOutputFeatureName: String

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    Definition Classes
    OpPipelineStage
  44. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  45. final def getTransientFeature(i: Int): Option[TransientFeature]

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    Definition Classes
    InputParams
  46. final def getTransientFeatures(): Array[TransientFeature]

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

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

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    Definition Classes
    Params
  49. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  50. implicit val i1Encoder: Encoder[features.types.RealNN.Value]

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    Definition Classes
    BinaryEstimator
  51. implicit val i2Encoder: Encoder[I2.Value]

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    Definition Classes
    BinaryEstimator
  52. final val impurity: Param[String]

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    Criterion used for information gain calculation (case-insensitive).

    Criterion used for information gain calculation (case-insensitive). Supported: "entropy" and "gini". (default = gini)

    Definition Classes
    DecisionTreeNumericBucketizerParams
  53. final def in1: TransientFeature

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    Attributes
    protected
    Definition Classes
    HasIn1
  54. final def in2: TransientFeature

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    Attributes
    protected
    Definition Classes
    HasIn2
  55. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

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

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

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    Definition Classes
    OpPipelineStage2 → InputParams
  58. final def isDefined(param: Param[_]): Boolean

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

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

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    Definition Classes
    Params
  61. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  62. def log: Logger

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

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  69. def logName: String

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  74. 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
  75. def makeVectorMetadata(input: TransientFeature, bucketLabels: Array[String], trackInvalid: Boolean, trackNulls: Boolean): OpVectorMetadata

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    Attributes
    protected
    Definition Classes
    NumericBucketizerMetadata
  76. final val maxBins: IntParam

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    Maximum number of bins Must be >= 2 and <= number of categories in any categorical feature.

    Maximum number of bins Must be >= 2 and <= number of categories in any categorical feature. (default = 32)

    Definition Classes
    DecisionTreeNumericBucketizerParams
  77. final val maxDepth: IntParam

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    Maximum depth of the tree (>= 0).

    Maximum depth of the tree (>= 0). E.g., depth 0 means 1 leaf node; depth 1 means 1 internal node + 2 leaf nodes. (default = 5)

    Definition Classes
    DecisionTreeNumericBucketizerParams
  78. final val minInfoGain: DoubleParam

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    Minimum information gain for a split to be considered at a tree node.

    Minimum information gain for a split to be considered at a tree node. Should be >= 0.0. (default = 0.0)

    Definition Classes
    DecisionTreeNumericBucketizerParams
  79. final val minInstancesPerNode: IntParam

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    Minimum number of instances each child must have after split.

    Minimum number of instances each child must have after split. If a split causes the left or right child to have fewer than minInstancesPerNode, the split will be discarded as invalid. Should be >= 1. (default = 1)

    Definition Classes
    DecisionTreeNumericBucketizerParams
  80. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  81. implicit val nev: Numeric[N]

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    numeric evidence for feature type value

  82. final def notify(): Unit

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

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    Definition Classes
    AnyRef
  84. def onGetMetadata(): Unit

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

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    Definition Classes
    VectorizerDefaults → InputParams
  86. 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
    BinaryEstimator → OpPipelineStageBase
  87. final def outputAsArray(out: OutputFeatures): Array[OPFeature]

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    Definition Classes
    OpPipelineStage → OpPipelineStageBase
  88. def outputFeatureUid: String

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    Attributes
    protected[com.salesforce.op]
    Definition Classes
    OpPipelineStage2 → OpPipelineStage
  89. def outputIsResponse: Boolean

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    Definition Classes
    AllowLabelAsInput → OpPipelineStage
  90. 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
  91. lazy val params: Array[Param[_]]

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

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

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

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

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    Definition Classes
    Params
  96. final def setDefault(paramPairs: ParamPair[_]*): DecisionTreeNumericBucketizer.this.type

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

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    Attributes
    protected
    Definition Classes
    Params
  98. final def setImpurity(value: Impurity): DecisionTreeNumericBucketizer.this.type

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  99. final def setInput(features: InputFeatures): DecisionTreeNumericBucketizer.this.type

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    Definition Classes
    OpPipelineStageBase
  100. final def setInputFeatures[S <: OPFeature](features: Array[S]): DecisionTreeNumericBucketizer.this.type

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    Attributes
    protected
    Definition Classes
    InputParams
  101. def setMaxBins(value: Int): DecisionTreeNumericBucketizer.this.type

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  102. def setMaxDepth(value: Int): DecisionTreeNumericBucketizer.this.type

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  103. final def setMetadata(m: Metadata): DecisionTreeNumericBucketizer.this.type

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    Definition Classes
    OpPipelineStageParams
  104. def setMinInfoGain(value: Double): DecisionTreeNumericBucketizer.this.type

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  105. def setMinInstancesPerNode(value: Int): DecisionTreeNumericBucketizer.this.type

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  106. def setOutputFeatureName(name: String): DecisionTreeNumericBucketizer.this.type

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    Definition Classes
    OpPipelineStage
  107. def setTrackInvalid(v: Boolean): DecisionTreeNumericBucketizer.this.type

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    Option to keep track of invalid values

    Option to keep track of invalid values

    Definition Classes
    TrackInvalidParam
  108. def setTrackNulls(v: Boolean): DecisionTreeNumericBucketizer.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
  109. final def stageName: String

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    Definition Classes
    OpPipelineStageBase
  110. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  111. def toString(): String

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

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    Definition Classes
    TrackInvalidParam
  113. final val trackNulls: BooleanParam

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    Definition Classes
    TrackNullsParam
  114. final def transformSchema(schema: StructType): StructType

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    Definition Classes
    OpPipelineStageBase
  115. def transformSchema(schema: StructType, logging: Boolean): StructType

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  116. implicit val tti1: scala.reflect.api.JavaUniverse.TypeTag[RealNN]

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    Definition Classes
    BinaryEstimator
  117. implicit val tti2: scala.reflect.api.JavaUniverse.TypeTag[I2]

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    type tag for numeric feature type

    type tag for numeric feature type

    Definition Classes
    BinaryEstimator
  118. implicit val ttiv1: scala.reflect.api.JavaUniverse.TypeTag[features.types.RealNN.Value]

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    Definition Classes
    BinaryEstimator
  119. implicit val ttiv2: scala.reflect.api.JavaUniverse.TypeTag[I2.Value]

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    type tag for numeric feature value type

    type tag for numeric feature value type

    Definition Classes
    BinaryEstimator
  120. implicit val tto: scala.reflect.api.JavaUniverse.TypeTag[OPVector]

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

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    Definition Classes
    BinaryEstimator → HasOut
  122. implicit val tupleEncoder: Encoder[(features.types.RealNN.Value, I2.Value)]

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    Definition Classes
    BinaryEstimator
  123. val uid: String

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    uid for instance

    uid for instance

    Definition Classes
    BinaryEstimator → Identifiable
  124. 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
  125. def vectorMetadataWithNullIndicators: OpVectorMetadata

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    Attributes
    protected
    Definition Classes
    VectorizerDefaults
  126. 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
  127. final def wait(): Unit

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

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

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

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    Definition Classes
    OpPipelineStageBase → MLWritable

Inherited from AllowLabelAsInput[OPVector]

Inherited from NumericBucketizerMetadata

Inherited from TrackNullsParam

Inherited from TrackInvalidParam

Inherited from VectorizerDefaults

Inherited from BinaryEstimator[RealNN, I2, OPVector]

Inherited from OpPipelineStage2[RealNN, I2, OPVector]

Inherited from HasOut[OPVector]

Inherited from HasIn2

Inherited from HasIn1

Inherited from OpPipelineStage[OPVector]

Inherited from OpPipelineStageBase

Inherited from MLWritable

Inherited from OpPipelineStageParams

Inherited from InputParams

Inherited from Estimator[BinaryModel[RealNN, I2, 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

getParam

param

setParam

Ungrouped