Class PhiCorrelationCoefficient
- java.lang.Object
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- elki.itemsetmining.associationrules.interest.PhiCorrelationCoefficient
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- All Implemented Interfaces:
InterestingnessMeasure
@Reference(authors="A. Agresti",title="Categorical Data Analysis",booktitle="Categorical Data Analysis",bibkey="books/wiley/Agresti90") @Reference(authors="P.-N. Tan, V. Kumar, J. Srivastava",title="Selecting the right objective measure for association analysis",booktitle="Information Systems 29.4",url="https://doi.org/10.1016/S0306-4379(03)00072-3",bibkey="DBLP:journals/is/TanKS04") public class PhiCorrelationCoefficient extends java.lang.Object implements InterestingnessMeasure
Phi Correlation Coefficient interestingness measure.\[ \frac{n P(X \cap Y) - P(X) - P(Y)}{\sqrt{P(X)P(Y)P(\neg X)P(\neg Y)}} \]
This is closely related to the χ² statistic.
The use for association rule mining was studied in:
P.-N. Tan, V. Kumar, J. Srivastava
Selecting the right objective measure for association analysis
Information Systems 29.4Tan et al. attribute this measure to:
A. Agresti
Categorical Data Analysis
Wiley Series in Probability and Statistics- Since:
- 0.8.0
- Author:
- Abhishek Sharma
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Constructor Summary
Constructors Constructor Description PhiCorrelationCoefficient()
Constructor.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description double
measure(int t, int sX, int sY, int sXY)
Computes the value of the measure for a given support values
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Method Detail
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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 interfaceInterestingnessMeasure
- Parameters:
t
- Total number of transactionsX
- Support of the antecedentsY
- Support of the consequentsXY
- Support of the union of antecedent and consequent- Returns:
- value of the measure
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