BIG MART SALES PREDICTION USING MACHINE LEARNING

Abstract

Today, supermarkets and supermarkets track sales data for each product to predict future customer demand and improve inventory management. The data warehouse contains a lot of customer data and a product specification in the data warehouse. Also extract archived data from archives to check for anomalies and regular patterns. Data obtained through machine learning from different stores like Big Mart can be used to predict future sales. In this paper, we present a forecasting model that uses XG boost Regressor technology to predict the sales of a company like Big Mart and find that the model has better performance than the existing model.