Class/Object

com.salesforce.op.stages.impl.selector

ModelSelectorSummary

Related Docs: object ModelSelectorSummary | package selector

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case class ModelSelectorSummary(validationType: ValidationType, validationParameters: Map[String, Any], dataPrepParameters: Map[String, Any], dataPrepResults: Option[SplitterSummary], evaluationMetric: EvalMetric, problemType: ProblemType, bestModelUID: String, bestModelName: String, bestModelType: String, validationResults: Seq[ModelEvaluation], trainEvaluation: EvaluationMetrics, holdoutEvaluation: Option[EvaluationMetrics]) extends MetadataLike with Product with Serializable

This is used to store all information about fitting and model selection generated by the model selector class

validationType

type of validation performed to select hyper parameters

validationParameters

parameters on validation

dataPrepParameters

parameters on data preparation before hyper parameter tuning

dataPrepResults

changes made to the data in data preparation

evaluationMetric

metric used to select hyper parameters and model

problemType

type of modeling (eg binary classification, regressionm etc)

bestModelUID

best model UID

validationResults

model with parameters and metric for all evaluated

trainEvaluation

winning model performance on training data set

holdoutEvaluation

winning model performance on holdout data set

Linear Supertypes
Serializable, Serializable, Product, Equals, MetadataLike, AnyRef, Any
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Inherited
  1. ModelSelectorSummary
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. MetadataLike
  7. AnyRef
  8. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new ModelSelectorSummary(validationType: ValidationType, validationParameters: Map[String, Any], dataPrepParameters: Map[String, Any], dataPrepResults: Option[SplitterSummary], evaluationMetric: EvalMetric, problemType: ProblemType, bestModelUID: String, bestModelName: String, bestModelType: String, validationResults: Seq[ModelEvaluation], trainEvaluation: EvaluationMetrics, holdoutEvaluation: Option[EvaluationMetrics])

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    validationType

    type of validation performed to select hyper parameters

    validationParameters

    parameters on validation

    dataPrepParameters

    parameters on data preparation before hyper parameter tuning

    dataPrepResults

    changes made to the data in data preparation

    evaluationMetric

    metric used to select hyper parameters and model

    problemType

    type of modeling (eg binary classification, regressionm etc)

    bestModelUID

    best model UID

    validationResults

    model with parameters and metric for all evaluated

    trainEvaluation

    winning model performance on training data set

    holdoutEvaluation

    winning model performance on holdout data set

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 ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  5. val bestModelName: String

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  6. val bestModelType: String

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  7. val bestModelUID: String

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    best model UID

  8. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  9. val dataPrepParameters: Map[String, Any]

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    parameters on data preparation before hyper parameter tuning

  10. val dataPrepResults: Option[SplitterSummary]

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    changes made to the data in data preparation

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

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    Definition Classes
    AnyRef
  12. val evaluationMetric: EvalMetric

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    metric used to select hyper parameters and model

  13. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  14. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any
  15. val holdoutEvaluation: Option[EvaluationMetrics]

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    winning model performance on holdout data set

  16. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  17. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  18. final def notify(): Unit

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    Definition Classes
    AnyRef
  19. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  20. val problemType: ProblemType

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    type of modeling (eg binary classification, regressionm etc)

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

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    Definition Classes
    AnyRef
  22. def toMetadata(): Metadata

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    Convert to metadata instance

    Convert to metadata instance

    Definition Classes
    ModelSelectorSummaryMetadataLike
  23. val trainEvaluation: EvaluationMetrics

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    winning model performance on training data set

  24. val validationParameters: Map[String, Any]

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    parameters on validation

  25. val validationResults: Seq[ModelEvaluation]

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    model with parameters and metric for all evaluated

  26. val validationType: ValidationType

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    type of validation performed to select hyper parameters

  27. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  28. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  29. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from MetadataLike

Inherited from AnyRef

Inherited from Any

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