Use of Machine Learning Models in Sales Forecasts
Shefali Jumnani1, Shraddha Agrawal2, Samiksha Verma3, Swasti Singhal4
1Shefali Jumnani, Information Technology, Galgotias College of Engineering and Technology, Greater Noida, India.
2Shraddha Agrawal, Information Technology, Galgotias College of Engineering and Technology, Greater Noida, India.
3Samiksha Verma, Information Technology, Galgotias College of Engineering and Technology, Greater Noida, India.
4Swasti Singhal, Information Technology, Galgotias College of Engineering and Technology, Greater Noida, India.
Manuscript received on May 04, 2020. | Revised Manuscript received on May 16, 2020. | Manuscript published on June 10, 2020. | PP: 66-69 | Volume-9 Issue-8, June 2020. | Retrieval Number: 100.1/ijitee.H6159069820 | DOI: 10.35940/ijitee.H6159.069820
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper, we present a brief survey of usage of various machine learning models and their role in retail sales forecasts. The purpose of this paper is to enlist a few popular approaches in retail sales and study their scope and areas of application. We analyze how these models have evolved over time stating the significance of each model in brief.
Keywords: Autoregressive integrated moving average, Artificial neural network, Random forests, Retail sales Forecasting, Support vector regression.
Scope of the Article: Machine Learning