org.pmml4s.model

AssociationRule

class AssociationRule extends HasPredictedValue with HasEntityId with HasConfidence with PmmlElement

We consider association rules of the form "<antecedent itemset> => <consequent itemset>" next:

Linear Supertypes
PmmlElement, Serializable, Serializable, HasExtensions, HasConfidence, HasEntityId, HasPredictedValue, AnyRef, Any
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Inherited
  1. AssociationRule
  2. PmmlElement
  3. Serializable
  4. Serializable
  5. HasExtensions
  6. HasConfidence
  7. HasEntityId
  8. HasPredictedValue
  9. AnyRef
  10. Any
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Instance Constructors

  1. new AssociationRule(antecedent: String, consequent: String, support: Double, confidence: Double, lift: Option[Double] = scala.None, leverage: Option[Double] = scala.None, affinity: Option[Double] = scala.None, id: Option[String] = scala.None)

    antecedent

    The id value of the itemset which is the antecedent of the rule. We represent the itemset by the letter A.

    consequent

    The id value of the itemset which is the consequent of the rule. We represent the itemset by the letter C.

    support

    The support of the rule, that is, the relative frequency of transactions that contain A and C: support(A->C) = support(A+C)

    confidence

    The confidence of the rule: confidence(A->C) = support(A+C) / support(A)

    lift

    A very popular measure of interestingness of a rule is lift. Lift values greater than 1.0 indicate that transactions containing A tend to contain C more often than transactions that do not contain A: lift(A->C) = confidence(A->C) / support(C)

    leverage

    Another measure of interestingness is leverage. An association with higher frequency and lower lift may be more interesting than an alternative rule with lower frequency and higher lift. The former can be more important in practice because it applies to more cases. The value is the difference between the observed frequency of A+C and the frequency that would be expected if A and C were independent: leverage(A->C) = support(A->C) - support(A)*support(C)

    affinity

    Also known as Jaccard Similarity, affinity is a measure of the transactions that contain both the antecedent and consequent (intersect) compared to those that contain the antecedent or the consequent (union): affinity(A->C) = support(A+C) / [ support(A) + support(C) - support(A+C)]

    id

    An identification to uniquely identify an association rule.

Value Members

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

    Definition Classes
    AnyRef
  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any
  3. final def ##(): Int

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

    Definition Classes
    AnyRef
  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any
  6. val affinity: Option[Double]

    Also known as Jaccard Similarity, affinity is a measure of the transactions that contain both the antecedent and consequent (intersect) compared to those that contain the antecedent or the consequent (union): affinity(A->C) = support(A+C) / [ support(A) + support(C) - support(A+C)]

  7. val antecedent: String

    The id value of the itemset which is the antecedent of the rule.

    The id value of the itemset which is the antecedent of the rule. We represent the itemset by the letter A.

  8. var antecedentItemset: Set[String]

  9. lazy val antecedentRule: String

  10. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  11. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  12. val confidence: Double

    The confidence of the rule: confidence(A->C) = support(A+C) / support(A)

    The confidence of the rule: confidence(A->C) = support(A+C) / support(A)

    Definition Classes
    AssociationRuleHasConfidence
  13. val consequent: String

    The id value of the itemset which is the consequent of the rule.

    The id value of the itemset which is the consequent of the rule. We represent the itemset by the letter C.

  14. var consequentItemset: Set[String]

  15. lazy val consequentRule: String

  16. def entityId: String

    Definition Classes
    AssociationRuleHasEntityId
  17. final def eq(arg0: AnyRef): Boolean

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

    Definition Classes
    AnyRef → Any
  19. def extensions: Seq[Extension]

    Definition Classes
    HasExtensions
  20. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  21. def fire(itemset: Set[String], algorithm: Algorithm): Boolean

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

    Definition Classes
    AnyRef → Any
  23. def hasExtensions: Boolean

    Definition Classes
    HasExtensions
  24. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  25. val id: Option[String]

    An identification to uniquely identify an association rule.

  26. var indexId: String

  27. def init(idToItemset: Map[String, Set[String]], index: Int): Unit

  28. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  29. val leverage: Option[Double]

    Another measure of interestingness is leverage.

    Another measure of interestingness is leverage. An association with higher frequency and lower lift may be more interesting than an alternative rule with lower frequency and higher lift. The former can be more important in practice because it applies to more cases. The value is the difference between the observed frequency of A+C and the frequency that would be expected if A and C were independent: leverage(A->C) = support(A->C) - support(A)*support(C)

  30. val lift: Option[Double]

    A very popular measure of interestingness of a rule is lift.

    A very popular measure of interestingness of a rule is lift. Lift values greater than 1.0 indicate that transactions containing A tend to contain C more often than transactions that do not contain A: lift(A->C) = confidence(A->C) / support(C)

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

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

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

    Definition Classes
    AnyRef
  34. def predictedValue: Any

    Definition Classes
    AssociationRuleHasPredictedValue
  35. lazy val rule: String

  36. val support: Double

    The support of the rule, that is, the relative frequency of transactions that contain A and C: support(A->C) = support(A+C)

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

    Definition Classes
    AnyRef
  38. def toString(): String

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

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

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from PmmlElement

Inherited from Serializable

Inherited from Serializable

Inherited from HasExtensions

Inherited from HasConfidence

Inherited from HasEntityId

Inherited from HasPredictedValue

Inherited from AnyRef

Inherited from Any

Ungrouped