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Applicable Metamorphic Testing for Erasable-Itemset Mining
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DOI：10.1109/ACCESS.2022.3165656.png)
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摘要
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Erasable-itemset mining is often used in production planning to identify itemsets that, if removed, would make little effect on the production profits. Consequently, much recent attention has been focused on increasing the mining efficiency. Yet, in addition to mining efficiency, guaranteeing mining correctness is also an important issue. In real applications, wrong mining results might lead a company to make inappropriate decisions. Therefore, in this paper, we use the metamorphic testing, a lightweight software-testing strategy, to check the mining results via discovering proper metamorphic relations. The core idea contains five metamorphic relations oriented from two aspects. In the first aspect, we alter maximum thresholds without changing the input data, and in the second aspect, we modify product databases and material items with fixing maximum thresholds. In the experiments, 11 datasets and 76 mutants generated by mu Java were used to discuss the effects of database parameters, including the average number of materials in products, the number of different material items, the number of products, and the maximum threshold, respectively. The experimental results show that the metamorphic relations deliver good assessment performances in terms of effectiveness and efficiency, especially the fourth metamorphic relation.
Keyword:
Data mining
erasable itemset
metamorphic testing
mining assessment
software testing
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
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引用论文
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METTLE: A METamorphic Testing Approach to Assessing and Validating Unsupervised Machine Learning SystemsMETTLE: 一种评估和验证无监督机器学习系统的变质测试方法
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