Research on Business District Operation Planning Based on Machine Learning

摘要

This paper applies machine learning core algorithms to business district operation planning to explore the attributes of retail performance and operational efficiency of Business District. This paper mainly uses K-Nearest Neighbor Algorithms to sort shops by their consumption records. Besides that it also uses K-means Clustering Algorithm and Association Rules Algorithm to cluster shop consumption types and uses association rules to find consumption association routes. Based on the above operation results, it can provide more accurate and effective data for business operators to make business district operation plans.