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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Ahmed Almaghthawi
King Khalid University
Computer Science & IT Engineering

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BMSP-ML: big mart sales prediction using different machine learning techniques Rao Faizan Ali; Amgad Muneer; Ahmed Almaghthawi; Amal Alghamdi; Suliman Mohamed Fati; Ebrahim Abdulwasea Abdullah Ghaleb
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 2: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v12.i2.pp874-883

Abstract

Variations in sales over time is the main issue faced by many retailers. To overcome this problem, we attempt to predict the sales by comparing the previous sales data of different stores. Firstly, the primary task is to recognize the pattern of the factors that help to predict sales. This study helps us understand the data and predict sales using many machines learning models. This process gets the data and beautifies the data by imputing the missing values and feature engineering. While solving this problem, predicting the monthly sales value is significant in the study. In addition, an essential element is to clear the missing data and perform proper feature engineering to better understand them before applying them. The experimental results show that the random forest predictor has outperformed ridge regression, linear regression, and decision tree models among the four machine learning techniques implemented in this study. The performance of the proposed models has been evaluated using root mean square error (RMSE).
Co-Authors Amal Alghamdi Amgad Muneer Ebrahim Abdulwasea Abdullah Ghaleb Rao Faizan Ali Suliman Mohamed Fati