文章基本信息

标题：Building Prediction Model using Market Basket Analysis
本地全文：下载
作者：Roshan Gangurde ; Dr. Binod Kumar ; Dr. S. D. Gore 等
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2017
卷号：5
期号：2
页码：2541
DOI：10.15680/IJIRCCE.2017.0502136
出版社：S&S Publications
摘要：In the recent years, analyzing shopping baskets turned out to be very appealing to retailers. Sophisticatedtechnology made it possible for them to collect information of their customers and what they purchase. Theintroduction of electronic point-of-sale expanded the utilization and application of transactional data in Market BasketAnalysis (MBA). In retail business, analyzing such information is exceedingly valuable for understanding purchasingbehavior. Mining purchasing patterns allows retailers to adjust promotions, store settings and serve consumers better.Predictive analysis is an advanced branch of data engineering which generally predicts some occurrence or probabilitybased on data. Predictive analytics uses data-mining techniques in order to make predictions about future events, andmake recommendations based on these predictions. The process involves an analysis of historic data and based on thatanalysis to predict the future occurrences or events. A model can be created to predict using Predictive Analyticsmodelling techniques. The form of these predictive models varies depending on the data they are using. PredictiveAnalytics is composed of various statistical & analytical techniques used to develop models that will predict futureoccurrence, events or probabilities. Predictive analytics is able to not only deal with continuous changes, butdiscontinuous changes as well. Classification, prediction, and to some extent, affinity analysis constitute the analyticalmethods employed in predictive analytics.
关键词：Association Rule Mining; Market Basket Analysis; Predictive Modelling