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, 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. RWrappable
  13. PythonWrappable
  14. BaseWrappable
  15. Transformer
  16. PipelineStage
  17. Logging
  18. Params
  19. Serializable
  20. Serializable
  21. Identifiable
  22. AnyRef
  23. 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. val evaluationMetric: Param[String]
    Definition Classes
    HasEvaluationMetric
  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. def getEvaluationMetric: String

    Definition Classes
    HasEvaluationMetric
  11. def getLabelCol: String

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

    Definition Classes
    HasScoredLabelsCol
  16. def getScoredProbabilitiesCol: String

    Definition Classes
    HasScoredProbabilitiesCol
  17. def getScoresCol: String

    Definition Classes
    HasScoresCol
  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. val labelCol: Param[String]

    The name of the label column

    The name of the label column

    Definition Classes
    HasLabelCol
  23. def logClass(featureName: String): Unit
    Definition Classes
    SynapseMLLogging
  24. def logFit[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: Option[Int] = None): T
    Definition Classes
    SynapseMLLogging
  27. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  28. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  29. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  30. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  31. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  32. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  33. val scoredLabelsCol: Param[String]

    The name of the scored labels column

    The name of the scored labels column

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

    The name of the scored probabilities column

    The name of the scored probabilities column

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

    The name of the scores column

    The name of the scores column

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

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

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

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

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

    Definition Classes
    HasScoresCol
  42. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  43. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    ComputePerInstanceStatistics → 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
    ComputePerInstanceStatistics → PipelineStage
  47. val uid: String
    Definition Classes
    ComputePerInstanceStatistics → SynapseMLLogging → Identifiable
  48. def write: MLWriter
    Definition Classes
    DefaultParamsWritable → MLWritable