Evolutionary operation setting for outcome accumulation type evolutionary rule discovery method
Evolutionary operation setting for outcome accumulation type evolutionary rule discovery method
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DOI：
10.1145/3520304.3528974
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发表时间：
2022-07
期刊：
影响因子：
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通讯作者：
Shogo Matsuno;K. Shimada
中科院分区：
文献类型：
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作者：
Shogo Matsuno;K. Shimada
关联规则分析作为数据挖掘的一种基本技术得到了广泛的应用。也进行了广泛的研究，将进化计算技术应用到数据挖掘领域。该研究提出了一种评估进化规则发现方法中进化操作设置的方法，其特点是通过小结果的获取和积累来执行整体问题的解决。由于种群进化的目的是不同的，从一般的进化计算方法，旨在发现精英个人，我们研究了在进化过程中的设置和评价的问题解决的进展和效率可视化的概念的差异。规则发现方法（GNMiner）的特点是在进化操作中反映获得的信息，本研究确定了进化操作的设置与每个任务执行阶段的进度和最终结果的实现之间的关系。本研究通过引入一个指数来可视化结果积累的效率，从而获得关于建立高效规则集发现的进化操作的方法的知识。这意味着在未来的研究中，在结果累积型进化计算中建立动态进化操作的可能性。
Association rule analysis has been widely employed as a basic technique for data mining. Extensive research has also been conducted to apply evolutionary computing techniques to the field of data mining. This study presents a method to evaluate the settings of evolutionary operations in evolutionary rule discovery method, which is characterized by the execution of overall problem solving through the acquisition and accumulation of small results. Since the purpose of population evolution is different from that of general evolutionary computation methods that aim at discovering elite individuals, we examined the difference in the concept of settings during evolution and the evaluation of evolutionary computation by visualizing the progress and efficiency of problem solving. The rule discovery method (GNMiner) is characterized by reflecting acquired information in evolutionary operations; this study determines the relationship between the settings of evolutionary operations and the progress of each task execution stage and the achievement of the final result. This study obtains knowledge on the means of setting up evolutionary operations for efficient rule-set discovery by introducing an index to visualize the efficiency of outcome accumulation. This implies the possibility of setting up dynamic evolutionary operations in the outcome accumulation-type evolutionary computation in future studies.