Big Mart Sales Prediction using Machine Learning

The traditional method of achieving sales and marketing objectives is outdated and no longer effective at helping businesses keep up with the fast-moving, competitive industry. With the advancement in machine learning, we looked into a number of machine learning techniques in our study that help the sales team design plans for expanding their business. The generated information can then be utilized to forecast possible sales volumes for merchants like Big Mart using a wide range of machine learning techniques. To estimate the output sales, machine learning models are fed this dataset of 8523 tuples and 12 different attributes that was obtained for big mart from the data source named Kaggle. We compared Linear Regression, AdaBoost Regressor and Random Forest regressor algorithms in this paper. Random Forest regressor performed best with the least Mean Squared Error (MSE) value of 1107.9451