de.lmu.ifi.dbs.elki.algorithm.itemsetmining.associationrules.interest

Class Confidence

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.itemsetmining.associationrules.interest.Confidence

All Implemented Interfaces:

InterestingnessMeasure

@Reference(authors="R. Agrawal, T. Imielinski, A. Swami",
           title="Mining association rules between sets of items in large databases",
           booktitle="Proc. ACM SIGMOD International Conference on Management of Data",
           url="https://doi.org/10.1145/170036.170072",
           bibkey="DBLP:conf/sigmod/AgrawalIS93")
public class Confidence
extends java.lang.Object
implements InterestingnessMeasure

Confidence interestingness measure, \( \tfrac{\text{support}(X \cup Y)}{\text{support}(X)} = \tfrac{P(X \cap Y)}{P(X)}=P(Y|X) \).

Reference:

R. Agrawal, T. Imielinski, A. Swami
Mining association rules between sets of items in large databases
Proc. ACM SIGMOD International Conference on Management of Data

Since:

0.7.5

Author:

Frederic Sautter

Constructor Summary

Constructors

Constructor and Description
Confidence() Constructor.

Method Summary

Modifier and Type	Method and Description
double	measure(int t, int sX, int sY, int sXY) Computes the value of the measure for a given support values

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Confidence

public Confidence()

Constructor.

Method Detail

measure

public double measure(int t,
                      int sX,
                      int sY,
                      int sXY)

Description copied from interface: InterestingnessMeasure

Computes the value of the measure for a given support values

Specified by:

measure in interface InterestingnessMeasure

Parameters:

t - Total number of transaction

sX - Support of the antecedent

sY - Support of the consequent

sXY - Support of the union of antecedent and consequent

Returns:

value of the measure