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Regression Algorithms for Big Mart Sales Prediction by trinhdo131200 is a document available to read on EtoBox.

This paper conducts a comparative analysis of various machine learning regression algorithms to predict sales for big mart companies, focusing on metrics such as correlation coefficient, mean absolute error, and root mean squared error. It discusses the importance of sales forecasting in retail management and evaluates techniques including SMO regression, random forest, and multi-layer perceptron. The findings aim to guide retailers in optimizing inventory management and enhancing customer satisfaction thro

Author

trinhdo131200

Language

EN