Class

org.pmml4s.model

NearestNeighborAttributes

Related Doc: package model

Permalink

class NearestNeighborAttributes extends ModelAttributes with HasNearestNeighborAttributes

Linear Supertypes
HasNearestNeighborAttributes, ModelAttributes, Serializable, Serializable, HasModelAttributes, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. NearestNeighborAttributes
  2. HasNearestNeighborAttributes
  3. ModelAttributes
  4. Serializable
  5. Serializable
  6. HasModelAttributes
  7. AnyRef
  8. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new NearestNeighborAttributes(functionName: MiningFunction, numberOfNeighbors: Int, continuousScoringMethod: ContScoringMethod = ContScoringMethod.average, categoricalScoringMethod: CatScoringMethod = CatScoringMethod.majorityVote, instanceIdVariable: Option[String] = None, threshold: Double = 0.001, modelName: Option[String] = None, algorithmName: Option[String] = None, isScorable: Boolean = true)

    Permalink

Value Members

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

    Permalink
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

    Permalink
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  4. val algorithmName: Option[String]

    Permalink

    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
    NearestNeighborAttributesModelAttributesHasModelAttributes
  5. final def asInstanceOf[T0]: T0

    Permalink
    Definition Classes
    Any
  6. val categoricalScoringMethod: CatScoringMethod

    Permalink

    Specify the scoring (or combining) method based on the categorical target values of K neighbors.

    Specify the scoring (or combining) method based on the categorical target values of K neighbors.

    Definition Classes
    NearestNeighborAttributesHasNearestNeighborAttributes
  7. def clone(): AnyRef

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. val continuousScoringMethod: ContScoringMethod

    Permalink

    Specify the scoring (or combining) method based on the continuous target values of K neighbors.

    Specify the scoring (or combining) method based on the continuous target values of K neighbors.

    Definition Classes
    NearestNeighborAttributesHasNearestNeighborAttributes
  9. final def eq(arg0: AnyRef): Boolean

    Permalink
    Definition Classes
    AnyRef
  10. def equals(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  11. def finalize(): Unit

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  12. val functionName: MiningFunction

    Permalink

    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
    NearestNeighborAttributesModelAttributesHasModelAttributes
  13. final def getClass(): Class[_]

    Permalink
    Definition Classes
    AnyRef → Any
  14. def hashCode(): Int

    Permalink
    Definition Classes
    AnyRef → Any
  15. val instanceIdVariable: Option[String]

    Permalink

    Contains the instance ID variable name and so refers to the name of a field in InstanceFields.

    Contains the instance ID variable name and so refers to the name of a field in InstanceFields. Required if the model has no targets, optional otherwise.

    Definition Classes
    NearestNeighborAttributesHasNearestNeighborAttributes
  16. def isAssociationRules: Boolean

    Permalink

    Tests if this is a association rules model.

    Tests if this is a association rules model.

    Definition Classes
    HasModelAttributes
  17. def isClassification: Boolean

    Permalink

    Tests if this is a classification model.

    Tests if this is a classification model.

    Definition Classes
    HasModelAttributes
  18. def isClustering: Boolean

    Permalink

    Tests if this is a clustering model.

    Tests if this is a clustering model.

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

    Permalink
    Definition Classes
    Any
  20. def isMixed: Boolean

    Permalink

    Tests if this is a mixed model.

    Tests if this is a mixed model.

    Definition Classes
    HasModelAttributes
  21. def isRegression: Boolean

    Permalink

    Tests if this is a regression model.

    Tests if this is a regression model.

    Definition Classes
    HasModelAttributes
  22. val isScorable: Boolean

    Permalink

    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
    NearestNeighborAttributesModelAttributesHasModelAttributes
  23. def isSequences: Boolean

    Permalink

    Tests if this is a sequences model.

    Tests if this is a sequences model.

    Definition Classes
    HasModelAttributes
  24. def isTimeSeries: Boolean

    Permalink

    Tests if this is a time series model.

    Tests if this is a time series model.

    Definition Classes
    HasModelAttributes
  25. val modelName: Option[String]

    Permalink

    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
    NearestNeighborAttributesModelAttributesHasModelAttributes
  26. final def ne(arg0: AnyRef): Boolean

    Permalink
    Definition Classes
    AnyRef
  27. final def notify(): Unit

    Permalink
    Definition Classes
    AnyRef
  28. final def notifyAll(): Unit

    Permalink
    Definition Classes
    AnyRef
  29. val numberOfNeighbors: Int

    Permalink

    Specifies K, the number of desired neighbors.

    Specifies K, the number of desired neighbors.

    Definition Classes
    NearestNeighborAttributesHasNearestNeighborAttributes
  30. final def synchronized[T0](arg0: ⇒ T0): T0

    Permalink
    Definition Classes
    AnyRef
  31. val threshold: Double

    Permalink

    Defines a very small positive number to be used for "weighted" scoring methods to avoid numerical problems when distance or similarity measure is zero.

    Defines a very small positive number to be used for "weighted" scoring methods to avoid numerical problems when distance or similarity measure is zero.

    Definition Classes
    NearestNeighborAttributesHasNearestNeighborAttributes
  32. def toString(): String

    Permalink
    Definition Classes
    AnyRef → Any
  33. final def wait(): Unit

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

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

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from ModelAttributes

Inherited from Serializable

Inherited from Serializable

Inherited from HasModelAttributes

Inherited from AnyRef

Inherited from Any

Ungrouped