Submit your paper : editorIJETjournal@gmail.com Paper Title : Prediction of Bigmart Sales using Machine Learning ISSN : 2395-1303 Year of Publication : 2022 10.5281/zenodo.7263461 MLA Style: -K. Kumara Swamy, G. Sathwika, A. Priyanka, A. Jyothsna Prediction of Bigmart Sales using Machine Learning , Volume 8 - Issue 5 September - October 2022 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org APA Style: -K. Kumara Swamy, G. Sathwika, A. Priyanka, A. Jyothsna Prediction of Bigmart Sales using Machine Learning , Volume 8 - Issue 5 September - October 2022 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org Abstract presently, supermarket run- centres, massive Marts keep track of every individual item's sales knowledge so as to anticipate potential client demand and update inventory management. Anomalies and general trends square measure usually discovered by mining {the knowledge the info the information} warehouse's data store. For retailers like massive mercantile establishment, the ensuing knowledge will be accustomed forecast future sales volume victimization numerous machine learning techniques like massive mercantile establishment. Reference [1] Ching Wu Chu and Guoqiang Peter Zhang, “A comparative study of linear and nonlinear models for aggregate retails sales forecasting”, Int. Journal Production Economics, vol. 86, pp. 217- 231, 2003. [2] Wang, Haoxiang. "Sustainable development and management in consumer electronics using soft computation." Journal of Soft Computing Paradigm (JSCP) 1, no. 01 (2019): 56.- 2. Suma, V., and Shavige Malleshwara Hills. "Data Mining based Prediction of D [3] Suma, V., and Shavige Malleshwara Hills. "Data Mining based Prediction of Demand in Indian Market for Refurbished Electronics." Journal of Soft Computing Paradigm (JSCP) 2, no. 02 (2020): 101- 110 [4] Giuseppe Nunnari, Valeria Nunnari, “Forecasting Monthly Sales Retail Time Series: A Case Study”, Proc. of IEEE Conf. on Business Informatics (CBI), July 2017. [5] https://halobi.com/blog/sales-forecasting- five-uses/. [Accessed: Oct. 3, 2018] [6] Zone-Ching Lin, Wen-Jang Wu, “Multiple LinearRegression Analysis of the Overlay Accuracy Model Zone”, IEEE Trans. on Semiconductor Manufacturing, vol. 12, no. 2, pp. 229 – 237, May 1999. [7] O. Ajao Isaac, A. Abdullahi Adedeji, I. Raji Ismail, “Polynomial Regression Model of Making Cost Prediction In Mixed Cost Analysis”, Int. Journal on Mathematical Theory and Modeling, vol. 2, no. 2, pp. 14 – 23, 2012. [8] C. Saunders, A. Gammerman and V. Vovk, “Ridge Regression Learning Algorithm in Dual Variables”, Proc. of Int. Conf. on Machine Learning, pp. 515 – 521, July 1998.IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 56, NO. 7, JULY 2010 3561. [9] ”Robust Regression and Lasso”. Huan Xu, Constantine Caramanis, Member, IEEE, and Shie Mannor, Senior Member, IEEE. 2015 International Conference on Industrial Informatics-Computing Technology, Intelligent Technology, Industrial Information Integration.”An improved Adaboost algorithm based on uncertain functions”.Shu Xinqing School of Automation Wuhan University of Technology.Wuhan, China Wang Pan School of the Automation Wuhan University of Technology Wuhan, China. [10] Xinqing Shu, Pan Wang, “An Improved Adaboost Algorithm based on Uncertain Functions”, Proc. of Int. Conf. on Industrial Informatics – Computing Technology, Intelligent Technology, Industrial Information Integration, Dec. 2015. [11] A. S. Weigend and N. A. Gershenfeld, “Time series prediction: Forecasting the future and understanding the past”, Addison-Wesley, 1994. [12] N. S. Arunraj, D. Ahrens, A hybrid seasonal autoregressive integrated moving average and quantile regression for daily food sales forecasting, Int. J. Production Economics 170 (2015) 321-335 Keywords — Prediction of Bigmart Sales using Machine Learning |