trait DoubleMLParams extends Params with HasTreatmentCol with HasOutcomeCol with HasFeaturesCol with HasMaxIter with HasWeightCol with HasParallelismInjected

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Inherited
  1. DoubleMLParams
  2. HasParallelismInjected
  3. HasParallelism
  4. HasWeightCol
  5. HasMaxIter
  6. HasFeaturesCol
  7. HasOutcomeCol
  8. HasTreatmentCol
  9. Params
  10. Serializable
  11. Serializable
  12. Identifiable
  13. AnyRef
  14. Any
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Abstract Value Members

  1. abstract def copy(extra: ParamMap): Params
    Definition Classes
    Params
  2. abstract val uid: String
    Definition Classes
    Identifiable

Concrete Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. def awaitFutures[T](futures: Array[Future[T]]): Seq[T]
    Attributes
    protected
    Definition Classes
    HasParallelismInjected
  7. final def clear(param: Param[_]): DoubleMLParams.this.type
    Definition Classes
    Params
  8. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  9. val confidenceLevel: DoubleParam
  10. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  11. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  12. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  13. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  14. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  15. def explainParams(): String
    Definition Classes
    Params
  16. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  17. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  18. val featuresCol: Param[String]

    The name of the features column

    The name of the features column

    Definition Classes
    HasFeaturesCol
  19. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  20. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  21. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  22. def getConfidenceLevel: Double
  23. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  24. def getExecutionContextProxy: ExecutionContext
    Definition Classes
    HasParallelismInjected
  25. def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol
  26. final def getMaxIter: Int
    Definition Classes
    HasMaxIter
  27. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  28. def getOutcomeCol: String
    Definition Classes
    HasOutcomeCol
  29. def getOutcomeModel: Estimator[_ <: Model[_]]
  30. def getParallelism: Int
    Definition Classes
    HasParallelism
  31. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  32. def getSampleSplitRatio: Array[Double]
  33. def getTreatmentCol: String
    Definition Classes
    HasTreatmentCol
  34. def getTreatmentModel: Estimator[_ <: Model[_]]
  35. def getWeightCol: String

    Definition Classes
    HasWeightCol
  36. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  37. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  38. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  39. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  40. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  41. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  42. final val maxIter: IntParam
    Definition Classes
    HasMaxIter
  43. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  44. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  45. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  46. val outcomeCol: Param[String]
    Definition Classes
    HasOutcomeCol
  47. val outcomeModel: EstimatorParam
  48. val parallelism: IntParam
    Definition Classes
    HasParallelism
  49. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  50. val sampleSplitRatio: DoubleArrayParam
  51. final def set(paramPair: ParamPair[_]): DoubleMLParams.this.type
    Attributes
    protected
    Definition Classes
    Params
  52. final def set(param: String, value: Any): DoubleMLParams.this.type
    Attributes
    protected
    Definition Classes
    Params
  53. final def set[T](param: Param[T], value: T): DoubleMLParams.this.type
    Definition Classes
    Params
  54. def setConfidenceLevel(value: Double): DoubleMLParams.this.type

    Set the higher bound percentile of ATE distribution.

    Set the higher bound percentile of ATE distribution. Default is 0.975. lower bound value will be automatically calculated as 100*(1-confidenceLevel) That means by default we compute 95% confidence interval, it is [2.5%, 97.5%] percentile of ATE distribution

  55. final def setDefault(paramPairs: ParamPair[_]*): DoubleMLParams.this.type
    Attributes
    protected
    Definition Classes
    Params
  56. final def setDefault[T](param: Param[T], value: T): DoubleMLParams.this.type
    Attributes
    protected
    Definition Classes
    Params
  57. def setFeaturesCol(value: String): DoubleMLParams.this.type

    Definition Classes
    HasFeaturesCol
  58. def setMaxIter(value: Int): DoubleMLParams.this.type

    Set the maximum number of confidence interval bootstrapping iterations.

    Set the maximum number of confidence interval bootstrapping iterations. Default is 1, which means it does not calculate confidence interval. To get Ci values please set a meaningful value

  59. def setOutcomeCol(value: String): DoubleMLParams.this.type

    Set name of the column which will be used as outcome

    Set name of the column which will be used as outcome

    Definition Classes
    HasOutcomeCol
  60. def setOutcomeModel(value: Estimator[_ <: Model[_]]): DoubleMLParams.this.type

    Set outcome model, it could be any model derived from 'org.apache.spark.ml.regression.Regressor' or 'org.apache.spark.ml.classification.ProbabilisticClassifier'

  61. def setParallelism(value: Int): DoubleMLParams.this.type
  62. def setSampleSplitRatio(value: Array[Double]): DoubleMLParams.this.type

    Set the sample split ratio, default is Array(0.5, 0.5)

  63. def setTreatmentCol(value: String): DoubleMLParams.this.type

    Set name of the column which will be used as treatment

    Set name of the column which will be used as treatment

    Definition Classes
    HasTreatmentCol
  64. def setTreatmentModel(value: Estimator[_ <: Model[_]]): DoubleMLParams.this.type

    Set treatment model, it could be any model derived from 'org.apache.spark.ml.regression.Regressor' or 'org.apache.spark.ml.classification.ProbabilisticClassifier'

  65. def setWeightCol(value: String): DoubleMLParams.this.type

    Definition Classes
    HasWeightCol
  66. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  67. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  68. val treatmentCol: Param[String]
    Definition Classes
    HasTreatmentCol
  69. val treatmentModel: EstimatorParam
  70. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  71. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  72. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  73. val weightCol: Param[String]

    The name of the weight column

    The name of the weight column

    Definition Classes
    HasWeightCol

Inherited from HasParallelismInjected

Inherited from HasParallelism

Inherited from HasWeightCol

Inherited from HasMaxIter

Inherited from HasFeaturesCol

Inherited from HasOutcomeCol

Inherited from HasTreatmentCol

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

getParam

param

setParam

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