AssociationRule

Instance Constructors

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

final def !=(arg0: Any): Boolean

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

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

Definition Classes
AnyRef → Any
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)]
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.
var antecedentItemset: Set[String]
lazy val antecedentRule: String
final def asInstanceOf[T0]: T0

Definition Classes
Any
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
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
AssociationRule → HasConfidence
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.
var consequentItemset: Set[String]
lazy val consequentRule: String
def entityId: String

Definition Classes
AssociationRule → HasEntityId
final def eq(arg0: AnyRef): Boolean

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

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

Definition Classes
HasExtensions
def finalize(): Unit

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

Definition Classes
AnyRef → Any
def hasExtensions: Boolean

Definition Classes
HasExtensions
def hashCode(): Int

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

An identification to uniquely identify an association rule.
var indexId: String
def init(idToItemset: Map[String, Set[String]], index: Int): Unit
final def isInstanceOf[T0]: Boolean

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

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
def predictedValue: Any

Definition Classes
AssociationRule → HasPredictedValue
lazy val rule: String
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)
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

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

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

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

Definition Classes
AnyRef
Annotations
@throws( ... )

Related Doc: package model

class AssociationRule extends HasPredictedValue with HasEntityId with HasConfidence with PmmlElement

Instance Constructors

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

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

val affinity: Option[Double]

val antecedent: String

var antecedentItemset: Set[String]

lazy val antecedentRule: String

final def asInstanceOf[T0]: T0

def clone(): AnyRef

val confidence: Double

val consequent: String

var consequentItemset: Set[String]

lazy val consequentRule: String

def entityId: String

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def extensions: Seq[Extension]

def finalize(): Unit

def fire(itemset: Set[String], algorithm: Algorithm): Boolean

final def getClass(): Class[_]

def hasExtensions: Boolean

def hashCode(): Int

val id: Option[String]

var indexId: String

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

final def isInstanceOf[T0]: Boolean

val leverage: Option[Double]

val lift: Option[Double]

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def predictedValue: Any

lazy val rule: String

val support: Double

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

def toString(): String

final def wait(): Unit

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

final def wait(arg0: Long): Unit

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