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], 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. HasIn2
  11. HasIn1
  12. OpPipelineStage
  13. OpPipelineStageBase
  14. MLWritable
  15. OpPipelineStageParams
  16. InputParams
  17. Estimator
  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 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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    Input Features type

    Input Features type

    Definition Classes
    OpPipelineStage2OpPipelineStageInputParams
  2. final type OutputFeatures = FeatureLike[OPVector]

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    Definition Classes
    OpPipelineStageOpPipelineStageBase
  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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    Checks the input length

    Checks the input length

    features

    input features

    returns

    true is input size as expected, false otherwise

    Definition Classes
    OpPipelineStage2InputParams
  8. 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
    BinaryEstimatorOpPipelineStageBase
  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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    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
  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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    Spark operation on dataset to produce RDD for constructor fit function and then turn output function into a Model

    Spark operation on dataset to produce RDD 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
    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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    Function that fits the binary model

    Function that fits the binary model

    Definition Classes
    DecisionTreeNumericBucketizerBinaryEstimator
  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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    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

  34. 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

  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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    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
    OpPipelineStage2OpPipelineStageBase
  43. 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
  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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    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
  46. final def getTransientFeatures(): Array[TransientFeature]

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    Gets the input Features

    Gets the input Features

    returns

    input features

    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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    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
    OpPipelineStage2InputParams
  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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    Function to be called on getMetadata

    Function to be called on getMetadata

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

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    Function to be called on setInput

    Function to be called on setInput

    Definition Classes
    VectorizerDefaultsOpPipelineStageBase
  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
    BinaryEstimatorOpPipelineStageBase
  87. 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
  88. def outputFeatureUid: String

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    Attributes
    protected[com.salesforce.op]
    Definition Classes
    OpPipelineStage2OpPipelineStage
  89. 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
    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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    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
  100. final def setInputFeatures[S <: OPFeature](features: Array[S]): DecisionTreeNumericBucketizer.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
  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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    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
  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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    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
  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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    type tag for first input

    type tag for first input

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

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    type tag for second input

    type tag for second input

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

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    type tag for first input value

    type tag for first input value

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

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    type tag for second input value

    type tag for second input value

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

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    type tag for output

    type tag for output

    Definition Classes
    BinaryEstimatorOpPipelineStage2
  121. 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
    BinaryEstimatorOpPipelineStage2
  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 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