[1]WANG Xueping,LIN Jiaxiang,WU Jianwei,et al.Adaptive-association-rule mining algorithm based on determination coefficient[J].CAAI Transactions on Intelligent Systems,2020,15(2):352-359.[doi:10.11992/tis.201809030]
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Adaptive-association-rule mining algorithm based on determination coefficient
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
15
Number of periods:
2020 2
Page number:
352-359
Column:
学术论文—人工智能基础
Public date:
2020-03-05
- Title:
- Adaptive-association-rule mining algorithm based on determination coefficient
- Keywords:
- association rule; order; adaptive; coefficient of determination; rule; support; confidence; curve fitting; polynomial; data mining
- CLC:
- TP391
- DOI:
- 10.11992/tis.201809030
- Abstract:
- The two-stage association-rule-mining algorithm based on the frequent item set generation and rule generation requires the manual assigning of minimum support and minimum confidence. To overcome this defect, this paper proposes a new method using the curve fitting technology based on the number of supports and confidence, in which the number of the order of curve and corresponding polynomial is automatically determined by a determination coefficient, which is called “adaptation association rule mining based on the determination coefficient R2” (AARM_BR). As the proposed AARM_BR method is driven by data, the thresholds of support and confi-dence can be automatically obtained. The experiments on two standard datasets Trolley and Groceries show that compared with a recently published method, the proposed method is more data-dependent and automatically determines the number of order of polynomial and the threshold of support and confidence under the circumstance of not having a priori knowledge.
- References:
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