Class/Object

com.microsoft.ml.spark

ComputePerInstanceStatistics

Related Docs: object ComputePerInstanceStatistics | package spark

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class ComputePerInstanceStatistics extends Transformer with ComputePerInstanceStatisticsParams

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
ComputePerInstanceStatisticsParams, HasEvaluationMetric, HasScoredProbabilitiesCol, HasScoredLabelsCol, HasScoresCol, HasLabelCol, DefaultParamsWritable, MLWritable, Wrappable, Transformer, PipelineStage, org.apache.spark.internal.Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. ComputePerInstanceStatistics
  2. ComputePerInstanceStatisticsParams
  3. HasEvaluationMetric
  4. HasScoredProbabilitiesCol
  5. HasScoredLabelsCol
  6. HasScoresCol
  7. HasLabelCol
  8. DefaultParamsWritable
  9. MLWritable
  10. Wrappable
  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
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Instance Constructors

  1. new ComputePerInstanceStatistics()

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  2. new ComputePerInstanceStatistics(uid: String)

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Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

  3. final def $[T](param: Param[T]): T

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    Attributes
    protected
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    Params

  4. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  6. final def clear(param: Param[_]): ComputePerInstanceStatistics.this.type

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    Definition Classes
    Params

  7. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  8. def copy(extra: ParamMap): Transformer

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    Definition Classes
    ComputePerInstanceStatistics → Transformer → PipelineStage → Params

  9. def copyValues[T <: Params](to: T, extra: ParamMap): T

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    Attributes
    protected
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    Params

  10. final def defaultCopy[T <: Params](extra: ParamMap): T

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    Attributes
    protected
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    Params

  11. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef

  12. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  13. val evaluationMetric: Param[String]

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    Definition Classes
    HasEvaluationMetric

  14. def explainParam(param: Param[_]): String

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    Definition Classes
    Params

  15. def explainParams(): String

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    Params

  16. final def extractParamMap(): ParamMap

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    Params

  17. final def extractParamMap(extra: ParamMap): ParamMap

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    Params

  18. def finalize(): Unit

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    protected[java.lang]
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    AnyRef
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    @throws( classOf[java.lang.Throwable] )

  19. final def get[T](param: Param[T]): Option[T]

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    Params

  20. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any

  21. final def getDefault[T](param: Param[T]): Option[T]

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    Definition Classes
    Params

  22. def getEvaluationMetric: String

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    Definition Classes
    HasEvaluationMetric

  23. def getLabelCol: String

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    Definition Classes
    HasLabelCol

  24. final def getOrDefault[T](param: Param[T]): T

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    Definition Classes
    Params

  25. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params

  26. def getScoredLabelsCol: String

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    Definition Classes
    HasScoredLabelsCol

  27. def getScoredProbabilitiesCol: String

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    Definition Classes
    HasScoredProbabilitiesCol

  28. def getScoresCol: String

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    Definition Classes
    HasScoresCol

  29. final def hasDefault[T](param: Param[T]): Boolean

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    Definition Classes
    Params

  30. def hasParam(paramName: String): Boolean

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    Params

  31. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  32. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

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    Attributes
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    Logging

  33. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Logging

  34. final def isDefined(param: Param[_]): Boolean

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  35. final def isInstanceOf[T0]: Boolean

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  36. final def isSet(param: Param[_]): Boolean

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  37. def isTraceEnabled(): Boolean

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    Logging

  38. val labelCol: Param[String]

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    The name of the label column

    The name of the label column

    Definition Classes
    HasLabelCol

  39. def log: Logger

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    Logging

  40. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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    Logging

  41. def logDebug(msg: ⇒ String): Unit

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    Logging

  42. def logError(msg: ⇒ String, throwable: Throwable): Unit

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    Logging

  43. def logError(msg: ⇒ String): Unit

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    Logging

  44. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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    Logging

  45. def logInfo(msg: ⇒ String): Unit

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    Logging

  46. def logName: String

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    Logging

  47. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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    Logging

  48. def logTrace(msg: ⇒ String): Unit

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    Logging

  49. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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    Logging

  50. def logWarning(msg: ⇒ String): Unit

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    Logging

  51. final def ne(arg0: AnyRef): Boolean

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    AnyRef

  52. final def notify(): Unit

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  53. final def notifyAll(): Unit

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    AnyRef

  54. lazy val params: Array[Param[_]]

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    Params

  55. def save(path: String): Unit

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    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )

  56. val scoredLabelsCol: Param[String]

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    The name of the scored labels column

    The name of the scored labels column

    Definition Classes
    HasScoredLabelsCol

  57. val scoredProbabilitiesCol: Param[String]

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    The name of the scored probabilities column

    The name of the scored probabilities column

    Definition Classes
    HasScoredProbabilitiesCol

  58. val scoresCol: Param[String]

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    The name of the scores column

    The name of the scores column

    Definition Classes
    HasScoresCol

  59. final def set(paramPair: ParamPair[_]): ComputePerInstanceStatistics.this.type

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    Attributes
    protected
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    Params

  60. final def set(param: String, value: Any): ComputePerInstanceStatistics.this.type

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    Params

  61. final def set[T](param: Param[T], value: T): ComputePerInstanceStatistics.this.type

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    Params

  62. final def setDefault(paramPairs: ParamPair[_]*): ComputePerInstanceStatistics.this.type

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  63. final def setDefault[T](param: Param[T], value: T): ComputePerInstanceStatistics.this.type

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    Params

  64. def setEvaluationMetric(value: String): ComputePerInstanceStatistics.this.type

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    Definition Classes
    HasEvaluationMetric

  65. def setLabelCol(value: String): ComputePerInstanceStatistics.this.type

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    Definition Classes
    HasLabelCol

  66. def setScoredLabelsCol(value: String): ComputePerInstanceStatistics.this.type

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    Definition Classes
    HasScoredLabelsCol

  67. def setScoredProbabilitiesCol(value: String): ComputePerInstanceStatistics.this.type

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    Definition Classes
    HasScoredProbabilitiesCol

  68. def setScoresCol(value: String): ComputePerInstanceStatistics.this.type

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    Definition Classes
    HasScoresCol

  69. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef

  70. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any

  71. def transform(dataset: Dataset[_]): DataFrame

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    Definition Classes
    ComputePerInstanceStatistics → Transformer

  72. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )

  73. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()

  74. def transformSchema(schema: StructType): StructType

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    Definition Classes
    ComputePerInstanceStatistics → PipelineStage

  75. def transformSchema(schema: StructType, logging: Boolean): StructType

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    Attributes
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    PipelineStage
    Annotations
    @DeveloperApi()

  76. val uid: String

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    Definition Classes
    ComputePerInstanceStatistics → Identifiable

  77. final def wait(): Unit

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    AnyRef
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    @throws( ... )

  78. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )

  79. final def wait(arg0: Long): Unit

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    @throws( ... )

  80. def write: MLWriter

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    Definition Classes
    DefaultParamsWritable → MLWritable

Inherited from ComputePerInstanceStatisticsParams

Inherited from HasEvaluationMetric

Inherited from HasScoredProbabilitiesCol

Inherited from HasScoredLabelsCol

Inherited from HasScoresCol

Inherited from HasLabelCol

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Wrappable

Inherited from Transformer

Inherited from PipelineStage

Inherited from org.apache.spark.internal.Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Parameters

A list of parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters

Parameter setters

Parameter getters

Members