Sales prediction using machine learning research paper. | Find, read and cite all the research you .

Sales prediction using machine learning research paper. This research presents an approach based on ML models, to infer sales pricing and analyse the causal relationships between the variables that influence future sales. A comprehensive study of sales prediction is done using Machine Learning models such as Linear Regression, K-Neighbors Regressor, XGBoost Regressor and Random Forest Regressor. This paper presents a comprehensive exploration of the methodology, techniques, and challenges associated with leveraging machine learning for sales forecasting. On the basis of a performance evaluation, a best suited predictive model is suggested for the sales trend forecast. : Conf For modern retail corporations operating a huge chain of businesses, exact sales predication is the key in driving corporations development, even success or failure. Ten research papers concentrating on various approaches for sales prediction are compared in this review paper. Regression techniques, including linear regression, Random Forest regressor, and XGBoost, were employed, along with the LSTM algorithm. The study explores various steps involved in data preprocessing, analysis, and model training using the XGBoost Regressor algorithm. Abstract : This research paper presents a machine learning-based approach for predicting sales in the retail sector, focusing on Big Mart as a case study. Dec 1, 2020 · Journal of Physics: Conference Series PAPER • OPEN ACCESS E-Commerce System for Sale Prediction Using Machine Learning Technique To cite this article: Karandeep Singh et al 2020 J. ous yf5ilu utnyuq bwpp ffhsl9gr bqak i0 u0 eir 1vmj