Abstract: Machine Learning has several category of algorithms that allows software applications to be more accurate in predicting results without being explicitly programmed. In this paper, the case of Big Mart, a one-stop-shopping center, has been discussed to predict the sales of different attributes, item varieties and for understanding the effects of different factors on the items’ sales. Considering various aspects of a dataset collected for Big Mart, methodology followed for constructing a predictive model, highly accurate results are generated, and these observations can be employed to take decisions to improve sales.
Keywords: Machine Learning, Sales Prediction, XGBoost Algorithm, Random Forest Algorithm, Linear Regression algorithm.
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DOI:
10.17148/IJARCCE.2023.124112
