Packages

class ComputePerInstanceStatistics extends Transformer with CPISParams with SynapseMLLogging

Evaluates the given scored dataset with per instance metrics.

The Regression metrics are: - L1_loss - L2_loss

The Classification metrics are: - log_loss

Linear Supertypes
SynapseMLLogging, CPISParams, HasEvaluationMetric, HasScoredProbabilitiesCol, HasScoredLabelsCol, HasScoresCol, HasLabelCol, DefaultParamsWritable, MLWritable, Wrappable, DotnetWrappable, RWrappable, PythonWrappable, BaseWrappable, Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. ComputePerInstanceStatistics
  2. SynapseMLLogging
  3. CPISParams
  4. HasEvaluationMetric
  5. HasScoredProbabilitiesCol
  6. HasScoredLabelsCol
  7. HasScoresCol
  8. HasLabelCol
  9. DefaultParamsWritable
  10. MLWritable
  11. Wrappable
  12. DotnetWrappable
  13. RWrappable
  14. PythonWrappable
  15. BaseWrappable
  16. Transformer
  17. PipelineStage
  18. Logging
  19. Params
  20. Serializable
  21. Serializable
  22. Identifiable
  23. AnyRef
  24. Any
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Visibility
  1. Public
  2. All

Instance Constructors

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

Value Members

  1. final def clear(param: Param[_]): ComputePerInstanceStatistics.this.type
    Definition Classes
    Params
  2. def copy(extra: ParamMap): Transformer
    Definition Classes
    ComputePerInstanceStatistics → Transformer → PipelineStage → Params
  3. def dotnetAdditionalMethods: String
    Definition Classes
    DotnetWrappable
  4. val evaluationMetric: Param[String]
    Definition Classes
    HasEvaluationMetric
  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 getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  11. def getEvaluationMetric: String

    Definition Classes
    HasEvaluationMetric
  12. def getLabelCol: String

    Definition Classes
    HasLabelCol
  13. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  14. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  15. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  16. def getScoredLabelsCol: String

    Definition Classes
    HasScoredLabelsCol
  17. def getScoredProbabilitiesCol: String

    Definition Classes
    HasScoredProbabilitiesCol
  18. def getScoresCol: String

    Definition Classes
    HasScoresCol
  19. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  20. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  21. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  22. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  23. val labelCol: Param[String]

    The name of the label column

    The name of the label column

    Definition Classes
    HasLabelCol
  24. def logClass(): Unit
    Definition Classes
    SynapseMLLogging
  25. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  26. def logTrain[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  27. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  28. def logVerb[T](verb: String, f: ⇒ T, columns: Int = -1): T
    Definition Classes
    SynapseMLLogging
  29. def makeDotnetFile(conf: CodegenConfig): Unit
    Definition Classes
    DotnetWrappable
  30. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  31. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  32. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  33. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  34. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  35. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  36. val scoredLabelsCol: Param[String]

    The name of the scored labels column

    The name of the scored labels column

    Definition Classes
    HasScoredLabelsCol
  37. val scoredProbabilitiesCol: Param[String]

    The name of the scored probabilities column

    The name of the scored probabilities column

    Definition Classes
    HasScoredProbabilitiesCol
  38. val scoresCol: Param[String]

    The name of the scores column

    The name of the scores column

    Definition Classes
    HasScoresCol
  39. final def set[T](param: Param[T], value: T): ComputePerInstanceStatistics.this.type
    Definition Classes
    Params
  40. def setEvaluationMetric(value: String): ComputePerInstanceStatistics.this.type

    Definition Classes
    HasEvaluationMetric
  41. def setLabelCol(value: String): ComputePerInstanceStatistics.this.type

    Definition Classes
    HasLabelCol
  42. def setScoredLabelsCol(value: String): ComputePerInstanceStatistics.this.type

    Definition Classes
    HasScoredLabelsCol
  43. def setScoredProbabilitiesCol(value: String): ComputePerInstanceStatistics.this.type

    Definition Classes
    HasScoredProbabilitiesCol
  44. def setScoresCol(value: String): ComputePerInstanceStatistics.this.type

    Definition Classes
    HasScoresCol
  45. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  46. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    ComputePerInstanceStatistics → Transformer
  47. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  48. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  49. def transformSchema(schema: StructType): StructType
    Definition Classes
    ComputePerInstanceStatistics → PipelineStage
  50. val uid: String
    Definition Classes
    ComputePerInstanceStatistics → SynapseMLLogging → Identifiable
  51. def write: MLWriter
    Definition Classes
    DefaultParamsWritable → MLWritable