Performance Comparison of Apriori and FP-Growth Techniques in Generating Association Rules to Prostate Cancer
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Creator Jaree Thongkam
Title Performance Comparison of Apriori and FP-Growth Techniques in Generating Association Rules to Prostate Cancer
Contributor Vatinee Sukmak, Phimaphot Sukmak
Publisher Faculyt of Informatics, Mahasarakham University
Publication Year 2561
Journal Title Journal of Applied Informatics and Technology
Journal Vol. 1
Journal No. 2
Page no. 103-111
Keyword Apriori, FP-Growth, Prostate Cancer, Association rule
URL Website https://ph01.tci-thaijo.org/index.php/jait/article/view/168672
Website title Journal of Applied Informatics and Technology
ISSN 2586-8136
Abstract Currently, the incidence of prostate cancer has been increasing around the world. Knowing prostate cancer survival time is very important for physicians and patients, since physicians can guide decision making in order to select the proper treatment that maximize benefit for each patient. This study aimed to compare Apriori and FP-Growth techniques in generating association rules to prostate cancer. The data were collected from SEER between January 2004 and 2014with the final 2,308 records. Apriori and FP-Growth techniques were used. The results showed that the FP-Growth technique has the ability to build more association rules than Apriori technique. The confidence of FP-Growth is 96.00% with 80-84.9% of support which is better than Apriori.
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