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, 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. RWrappable
  5. PythonWrappable
  6. BaseWrappable
  7. DefaultParamsWritable
  8. MLWritable
  9. HasOutputCol
  10. Transformer
  11. PipelineStage
  12. Logging
  13. Params
  14. Serializable
  15. Serializable
  16. Identifiable
  17. AnyRef
  18. Any
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Visibility
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  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 explainParam(param: Param[_]): String
    Definition Classes
    Params
  4. def explainParams(): String
    Definition Classes
    Params
  5. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  6. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  7. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  8. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  9. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  10. final def getOutcomeResidualCol: String
  11. def getOutputCol: String

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

    The name of the output column

    The name of the output column

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

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