How to Determine Minimum Support in Association Rule

Erna Hikmawati, K. Surendro
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引用次数: 7

Abstract

The growth of increasingly complex data now raises new challenges in the world of technology. Large volumes of data store a lot of knowledge that can help in the decision-making process. One way to find knowledge in big data is by the Association Rule. The association rule is a technique in data mining that can produce rules based on the frequency of items appearing from a transactional database. One thing that is critical in the association rule is the determination of the minimum support value used to determine which items will be included in the formation of rules. If the minimum support value that is set is too small, it causes too many items to be involved in establishing the rules. Conversely, if the minimum support is too large, the number of items involved in forming the rule is too small. The problem in determining the minimum support value greatly affects the accuracy of the resulting rule. In this paper, various methods will be discussed to determine the minimum value of support through study literature based on related research. In addition, it explains research opportunities that can be done in the future about the minimum value of support determination in the association rule.
如何确定关联规则的最小支持度
日益复杂的数据增长现在给技术世界带来了新的挑战。大量的数据存储了大量的知识,可以帮助决策过程。在大数据中寻找知识的一种方法是通过关联规则。关联规则是数据挖掘中的一种技术,它可以根据事务数据库中出现的项的频率生成规则。关联规则中至关重要的一件事是确定用于确定哪些项将包含在规则形成中的最小支持值。如果设置的最小支持值太小,则会导致在建立规则时涉及太多的项。相反,如果最小支持太大,则形成规则所涉及的项目数量太少。确定最小支持值的问题极大地影响了所得规则的准确性。本文将在相关研究的基础上,通过研究文献探讨确定最小支持值的各种方法。此外,本文还阐述了关联规则中支持度确定最小值的研究机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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