Abstract
The typical model, which involves the measures: support, confidence, and interest, is often adapted to mining association rules. In the model, the related parameters are usually chosen by experience; consequently, the number of useful rules is hard to estimate. If the number is too large, we cannot effectively extract the meaningful rules. This paper analyzes the meanings of the parameters and designs a variety of equations between the number of rules and the parameters by using regression method. Finally, we experimentally obtain a preferable regression equation. This paper uses multiple correlation coefficients to test the fitting effects of the equations and uses significance test to verify whether the coefficients of parameters are significantly zero or not. The regression equation that has a larger multiple correlation coefficient will be chosen as the optimally fitted equation. With the selected optimal equation, we can predict the number of rules under the given parameters and further optimize the choice of the three parameters and determine their ranges of values.
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This work was supported by the National Natural Science Foundation of China (No. J07240003, No. 60773084, No. 60603023) and National Research Fund for the Doctoral Program of Higher Education of China (No. 20070151009).
Wei-Guo Yi graduated from Northeast Normal University, PRC in 2002. He received the M. Sc. degree from Northeast Normal University in 2005. He is a lecturer of Dalian Jiaotong University, PRC. Currently, he is a Ph.D. candidate at the School of Information Science and Technology, Dalian Maritime University, Dalian, PRC.
His research interests include data mining and pattern recognition.
Ming-Yu Lu graduated from Heilongjiang University of Computer Software, PRC in 1985. He received the M. Sc. degree in 1988 and the Ph.D. degree in 2003, both from Tsinghua University, PRC. He is a senior member of the China Computer Federation and professor of Dalian Maritime University, PRC.
His research interests include data mining, text mining, and Web mining.
Zhi Liu graduated from Dalian University, PRC in 1995. She received the M. Sc. degree from Dalian University of Technology, PRC in 1999. She is an associate professor of Dalian Maritime University, PRC. Currently, she is a Ph. D. candidate at the School of Information Science and Technology, Dalian Maritime University.
Her research interests include data mining and artificial intelligence.
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Yi, WG., Lu, MY. & Liu, Z. Regression analysis of the number of association rules. Int. J. Autom. Comput. 8, 78–82 (2011). https://doi.org/10.1007/s11633-010-0557-x
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DOI: https://doi.org/10.1007/s11633-010-0557-x