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

Compute the differences between observed and predicted values of data. for classification, we compute residual as "observed - probability($(classIndex))" for regression, we compute residual as "observed - prediction"

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. ResidualTransformer
  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 ResidualTransformer()
  2. new ResidualTransformer(uid: String)

Value Members

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

    Definition Classes
    HasOutputCol
  15. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  16. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  17. final def getPredictedCol: String
  18. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  19. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  20. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  21. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  22. def logClass(): Unit
    Definition Classes
    SynapseMLLogging
  23. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  24. def logTrain[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  25. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  26. def logVerb[T](verb: String, f: ⇒ T, columns: Int = -1): T
    Definition Classes
    SynapseMLLogging
  27. def makeDotnetFile(conf: CodegenConfig): Unit
    Definition Classes
    DotnetWrappable
  28. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  29. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  30. val observedCol: Param[String]
  31. val outputCol: Param[String]

    The name of the output column

    The name of the output column

    Definition Classes
    HasOutputCol
  32. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  33. val predictedCol: Param[String]
  34. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  35. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  36. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  37. final def set[T](param: Param[T], value: T): ResidualTransformer.this.type
    Definition Classes
    Params
  38. def setClassIndex(value: Int): ResidualTransformer.this.type
  39. def setObservedCol(value: String): ResidualTransformer.this.type
  40. def setOutputCol(value: String): ResidualTransformer.this.type

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