About this document
Retail Sales Forecasting with ML Techniques by faizamahbub99 is a document available to read on EtoBox.
This paper explores predictive analysis of retail sales forecasting using various machine learning techniques, focusing on the Citadel POS dataset from 2013 to 2018. The study compares multiple regression and time series models, concluding that Xgboost provides the best performance for sales forecasting with a MAE of 0.516 and RMSE of 0.63. The research emphasizes the importance of accurate sales forecasting for inventory management and business planning in the retail industry.
- Author
- faizamahbub99
- Language
- EN