Research on Location of Chain Convenience Stores Based on Machine Learning

Abstract

As an entity retail business that mainly meets customer convenience, City chain convenience stores have achieved rapid development. In order to provide better service, merchants mainly rely on the choice of better convenience store address besides the refinement of business technology. Compared with the traditional location strategy based on analytic hierarchy process, urban big data brings a new way of thinking. Based on the data of Meituan.com, Lianjia.com and Amap.com, this paper takes Beijing 7-ELEVEN Convenience Store as the research object, combines three machine learning algorithms to classify and predict the locations of Beijing's various regions, obtains the location prediction model of urban chain convenience stores, and evaluates the performance of the model.