class OrthoForestVariableTransformer extends Transformer with HasOutputCol with DefaultParamsWritable with Wrappable with SynapseMLLogging

Transform the outcome residual and treatment residual. \E_n\left[ \left(\tilde{Y} - \theta(X) \cdot \tilde{T}\right)2 \right] = \E_n\left[ \tilde{T}2 \left(\frac{\tilde{Y}}{\tilde{T}} - \theta(X)\right)^2 \right] The latter corresponds to a weighted regression problem, where the target label is :math:\tilde{Y}/\tilde{T}, the features are X and the weight of each sample is :math:\tilde{T}^2. Any regressor that accepts sample weights can be used as a final model, e.g.:

Linear Supertypes
SynapseMLLogging, Wrappable, DotnetWrappable, RWrappable, PythonWrappable, BaseWrappable, DefaultParamsWritable, MLWritable, HasOutputCol, Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. OrthoForestVariableTransformer
  2. SynapseMLLogging
  3. Wrappable
  4. DotnetWrappable
  5. RWrappable
  6. PythonWrappable
  7. BaseWrappable
  8. DefaultParamsWritable
  9. MLWritable
  10. HasOutputCol
  11. Transformer
  12. PipelineStage
  13. Logging
  14. Params
  15. Serializable
  16. Serializable
  17. Identifiable
  18. AnyRef
  19. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new OrthoForestVariableTransformer()
  2. new OrthoForestVariableTransformer(uid: String)

Value Members

  1. final def clear(param: Param[_]): OrthoForestVariableTransformer.this.type
    Definition Classes
    Params
  2. def copy(extra: ParamMap): OrthoForestVariableTransformer
    Definition Classes
    OrthoForestVariableTransformer → Transformer → PipelineStage → Params
  3. def dotnetAdditionalMethods: String
    Definition Classes
    DotnetWrappable
  4. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  5. def explainParams(): String
    Definition Classes
    Params
  6. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  7. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  8. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  9. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  10. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  11. final def getOutcomeResidualCol: String
  12. def getOutputCol: String

    Definition Classes
    HasOutputCol
  13. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  14. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  15. final def getTreatmentResidualCol: String
  16. final def getWeightsCol: String
  17. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  18. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  19. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  20. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  21. def logClass(featureName: String): Unit
    Definition Classes
    SynapseMLLogging
  22. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  23. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  24. def logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): T
    Definition Classes
    SynapseMLLogging
  25. def makeDotnetFile(conf: CodegenConfig): Unit
    Definition Classes
    DotnetWrappable
  26. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  27. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  28. val outcomeResidualCol: Param[String]
  29. val outputCol: Param[String]

    The name of the output column

    The name of the output column

    Definition Classes
    HasOutputCol
  30. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  31. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  32. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  33. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  34. final def set[T](param: Param[T], value: T): OrthoForestVariableTransformer.this.type
    Definition Classes
    Params
  35. def setOutcomeResidualCol(value: String): OrthoForestVariableTransformer.this.type
  36. def setOutputCol(value: String): OrthoForestVariableTransformer.this.type

    Definition Classes
    HasOutputCol
  37. def setTreatmentResidualCol(value: String): OrthoForestVariableTransformer.this.type
  38. def setWeightsCol(value: String): OrthoForestVariableTransformer.this.type
  39. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  40. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    OrthoForestVariableTransformer → Transformer
  41. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  42. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  43. def transformSchema(schema: StructType): StructType
    Definition Classes
    OrthoForestVariableTransformer → PipelineStage
  44. val treatmentResidualCol: Param[String]
  45. val uid: String
    Definition Classes
    OrthoForestVariableTransformer → SynapseMLLogging → Identifiable
  46. val weightsCol: Param[String]
  47. def write: MLWriter
    Definition Classes
    DefaultParamsWritable → MLWritable