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.


Downloads: PDF | DOI: 10.17148/IJARCCE.2023.124112

How to Cite:

[1] Sathyanarayana S, Apeksha C, Chethana S, Chinmayee H C, Abhishree G L, "BIG MART SALES PREDICTION USING MACHINE LEARNING," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2023.124112

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