smile.association

Class AssociationRule

java.lang.Object

smile.association.AssociationRule

public class AssociationRule
extends java.lang.Object

Association rule object. Let I = {i₁, i₂,..., i_n} be a set of n binary attributes called items. Let D = {t₁, t₂,..., t_m} be a set of transactions called the database. Each transaction in D has a unique transaction ID and contains a subset of the items in I. An association rule is defined as an implication of the form X ⇒ Y where X, Y ⊆ I and X ∩ Y = Ø. The item sets X and Y are called antecedent (left-hand-side or LHS) and consequent (right-hand-side or RHS) of the rule, respectively. The support supp(X) of an item set X is defined as the proportion of transactions in the database which contain the item set. Note that the support of an association rule X ⇒ Y is supp(X ∪ Y). The confidence of a rule is defined conf(X ⇒ Y) = supp(X ∪ Y) / supp(X). Confidence can be interpreted as an estimate of the probability P(Y | X), the probability of finding the RHS of the rule in transactions under the condition that these transactions also contain the LHS.

Field Summary

Fields

Modifier and Type	Field and Description
int[]	antecedent Antecedent itemset.
double	confidence The confidence value.
int[]	consequent Consequent itemset.
double	support The support value.

Constructor Summary

Constructors

Constructor and Description
AssociationRule(int[] antecedent, int[] consequent, double support, double confidence) Constructor.

Method Summary

Modifier and Type	Method and Description
boolean	equals(java.lang.Object o)
int	hashCode()
java.lang.String	toString()

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Field Detail

antecedent

public final int[] antecedent

Antecedent itemset.

consequent

public final int[] consequent

Consequent itemset.

support

public final double support

The support value. The support supp(X) of an itemset X is defined as the proportion of transactions in the database which contain the itemset.

confidence

public final double confidence

The confidence value. The confidence of a rule is defined conf(X ⇒ Y) = supp(X ∪ Y) / supp(X). Confidence can be interpreted as an estimate of the probability P(Y | X), the probability of finding the RHS of the rule in transactions under the condition that these transactions also contain the LHS.

Constructor Detail

AssociationRule

public AssociationRule(int[] antecedent,
                       int[] consequent,
                       double support,
                       double confidence)

Constructor.

Parameters:

antecedent - the antecedent itemset (LHS) of the association rule.

consequent - the consequent itemset (RHS) of the association rule.

support - the associated support value.

confidence - the associated confidence value.

Method Detail

equals

public boolean equals(java.lang.Object o)

Overrides:

equals in class java.lang.Object

hashCode

public int hashCode()

Overrides:

hashCode in class java.lang.Object

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object