Paper Title: PREDICTING FUTURE SALES OF BIG MART WITH MACHINE LEARNING ALGORITHMS

Author's name: R. Mugesh, Uma Maheswari G

The big mart sales analysis patterns are seen as an important activity and it is more effective. Hence, big mart prices will lead to lucrative profits from sound taking decisions. Therefore, forecasting the big market is a major challenge for investors to use their money to make more profit. Research questions are used to guide the selection of the studies. Hence, these selected studies are helping to find the ML techniques along with their data set for big mart sales prediction. big super market sales prediction using machine learning algorithm, many supermarkets today do not have a good forecast of their yearly sales. This is mostly due to the lack of proficiency, resources and knowledge to make sales estimation. To analyses and forecast sales for the upcoming year, the majority of grocery chains utilize, at best, a set of tools and procedures. There are many problems with using traditional statistical methods to estimate supermarket sales, and they frequently lead to the development of prediction models with subpar performance. The sales projection is based on Big Mart sales from various locations in order to adjust the company strategy to the anticipated outcomes. Then, various machine learning techniques may be used to project potential sales volumes for retailers like Big Mart. Machine Learning models such as Random Forest, Xgboost, Light Gradient Boosting Machine are used in detailed research of sales prediction.

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