Comparative Study Of APRIORI and FP Algorithm For Decision Making

J. Sivapriya, Rohit Roy, Mayukh Biswas, Sangram Mandal
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引用次数: 3

Abstract

Decision Making is one of the hardest and most crucial skill and as there are many tools to support the leader of big companies to make an error free decisions, but ever since data mining has arrived in the world of business the job of such leaders has become much more crucial in order to take best decision. Apriori and FP Growth are two widely used algorithm to predict the data. These algorithm are used to do extensive research on the frequent itemsets in order to get possible results. This research contributes as an insight in selective perception on how we can prowess the apt of decision making using business analytics and data mining creating all the possible models and warnings for the leader of the company to take best fit decisions as per the given problem statement.
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APRIORI与FP算法在决策中的比较研究
决策是最困难也是最关键的技能之一,因为有许多工具可以帮助大公司的领导者做出无错误的决策,但自从数据挖掘进入商业世界以来,这些领导者的工作变得更加重要,以便做出最佳决策。Apriori和FP Growth是两种被广泛使用的数据预测算法。这些算法用于对频繁项集进行广泛的研究,以获得可能的结果。这项研究有助于洞察选择性感知,即我们如何利用业务分析和数据挖掘来提高决策能力,为公司领导人创建所有可能的模型和警告,以便根据给定的问题陈述做出最合适的决策。
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