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, 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. 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
  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 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 getClassIndex: Int
  10. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  11. final def getObservedCol: String
  12. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  13. def getOutputCol: String

    Definition Classes
    HasOutputCol
  14. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  15. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  16. final def getPredictedCol: 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 makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  26. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  27. val observedCol: Param[String]
  28. val outputCol: Param[String]

    The name of the output column

    The name of the output column

    Definition Classes
    HasOutputCol
  29. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  30. val predictedCol: Param[String]
  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): ResidualTransformer.this.type
    Definition Classes
    Params
  35. def setClassIndex(value: Int): ResidualTransformer.this.type
  36. def setObservedCol(value: String): ResidualTransformer.this.type
  37. def setOutputCol(value: String): ResidualTransformer.this.type

    Definition Classes
    HasOutputCol
  38. def setPredictedCol(value: String): ResidualTransformer.this.type
  39. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  40. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    ResidualTransformer → 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
    ResidualTransformer → PipelineStage
  44. val uid: String
    Definition Classes
    ResidualTransformer → SynapseMLLogging → Identifiable
  45. def write: MLWriter
    Definition Classes
    DefaultParamsWritable → MLWritable