Paper Title
Machine Learning in Demand Forecasting for Retail
Abstract
This article presents a strategy for anticipating consumer demand based on essential indicators and the target
variable. These models are based on traditional and contemporary techniques for predicting time series. Our proposed
demand forecasting model is based on working with panel samples, clustering time series that are generated based on
starting data of economic factors, and using machine learning techniques. The proposed models were tested using
conventional regression performance metrics.
Keywords - Machine Learning, Forecasting, Recommendation System, Retail Demand