Trait

org.pmml4s.model

HasWrappedRegressionAttributes

Related Doc: package model

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trait HasWrappedRegressionAttributes extends HasWrappedModelAttributes with HasRegressionAttributes

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  1. HasWrappedRegressionAttributes
  2. HasRegressionAttributes
  3. HasWrappedModelAttributes
  4. HasModelAttributes
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Abstract Value Members

  1. abstract def attributes: RegressionAttributes

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    Common attributes of this model

    Common attributes of this model

    Definition Classes
    HasWrappedRegressionAttributesHasWrappedModelAttributes

Concrete Value Members

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

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  2. final def ##(): Int

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

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  4. def algorithmName: Option[String]

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    The algorithm name is free-type and can be any description for the specific algorithm that produced the model.

    The algorithm name is free-type and can be any description for the specific algorithm that produced the model. This attribute is for information only.

    Definition Classes
    HasWrappedModelAttributesHasModelAttributes
  5. final def asInstanceOf[T0]: T0

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  6. def clone(): AnyRef

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    Attributes
    protected[java.lang]
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    @throws( ... )
  7. final def eq(arg0: AnyRef): Boolean

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  8. def equals(arg0: Any): Boolean

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  9. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  10. def functionName: MiningFunction

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    Describe the kind of mining model, e.g., whether it is intended to be used for clustering or for classification.

    Describe the kind of mining model, e.g., whether it is intended to be used for clustering or for classification.

    Definition Classes
    HasWrappedModelAttributesHasModelAttributes
  11. final def getClass(): Class[_]

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  12. def hashCode(): Int

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  13. def isAssociationRules: Boolean

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    Tests if this is a association rules model.

    Tests if this is a association rules model.

    Definition Classes
    HasModelAttributes
  14. def isClassification: Boolean

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    Tests if this is a classification model.

    Tests if this is a classification model.

    Definition Classes
    HasModelAttributes
  15. def isClustering: Boolean

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    Tests if this is a clustering model.

    Tests if this is a clustering model.

    Definition Classes
    HasModelAttributes
  16. final def isInstanceOf[T0]: Boolean

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  17. def isMixed: Boolean

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    Tests if this is a mixed model.

    Tests if this is a mixed model.

    Definition Classes
    HasModelAttributes
  18. def isRegression: Boolean

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    Tests if this is a regression model.

    Tests if this is a regression model.

    Definition Classes
    HasModelAttributes
  19. def isScorable: Boolean

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    Indicates if the model is valid for scoring.

    Indicates if the model is valid for scoring. If this attribute is true or if it is missing, then the model should be processed normally. However, if the attribute is false, then the model producer has indicated that this model is intended for information purposes only and should not be used to generate results.

    Definition Classes
    HasWrappedModelAttributesHasModelAttributes
  20. def isSequences: Boolean

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    Tests if this is a sequences model.

    Tests if this is a sequences model.

    Definition Classes
    HasModelAttributes
  21. def isTimeSeries: Boolean

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    Tests if this is a time series model.

    Tests if this is a time series model.

    Definition Classes
    HasModelAttributes
  22. def modelName: Option[String]

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    Identifies the model with a unique name in the context of the PMML file.

    Identifies the model with a unique name in the context of the PMML file. This attribute is not required. Consumers of PMML models are free to manage the names of the models at their discretion.

    Definition Classes
    HasWrappedModelAttributesHasModelAttributes
  23. def modelType: Option[RegressionModelType]

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

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  25. def normalizationMethod: RegressionNormalizationMethod

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  26. final def notify(): Unit

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  27. final def notifyAll(): Unit

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

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  29. def targetFieldName: Option[String]

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    The name of the target field (also called dependent variable).

    The name of the target field (also called dependent variable). The attribute targetFieldName is for information only.

    Definition Classes
    HasWrappedRegressionAttributesHasRegressionAttributes
  30. def toString(): String

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  31. final def wait(): Unit

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    @throws( ... )
  32. final def wait(arg0: Long, arg1: Int): Unit

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

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Inherited from HasRegressionAttributes

Inherited from HasWrappedModelAttributes

Inherited from HasModelAttributes

Inherited from AnyRef

Inherited from Any

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