Predictive Analysis for Big Mart Sales Using Machine Learning Algorithms

Abstract: Supermarkets and retail giants like Big Mart rely heavily on tracking individual item sales data to anticipate consumer demand and optimize inventory management. By mining data warehouses, anomalies, and trends can be identified, providing valuable insights for forecasting future sales volumes. Leveraging advanced machine learning techniques, such as Decision Tree Regression, predictive models can be developed to forecast sales accurately. Through the implementation of such a model, it has been observed that it surpasses the performance of existing forecasting models. This innovative approach not only enhances decision-making processes but also enables businesses like Big Mart to stay ahead in a competitive market landscape.