Shopping malls and Big Marts keep track of individual item sales, consumer information, and item details in a data warehouse to forecast future demand. Train data with Random Forest gives less as it gives mean square error. then others i.e. 1058.
Nowadays, shopping malls and Big Marts keep track of individual item sales data in order to forecast future client demand and adjust inventory management. In a data warehouse, these data stores hold a significant amount of consumer information and particular item details. By mining the data store from the data warehouse, more anomalies and common patterns can be discovered.
I am using a public dataset of Big Mart Prediction from the Kaggle.
URL: https://www.kaggle.com/datasets/brijbhushannanda1979/bigmart-sales-data?select=Train.csv
Notebook: https://github.com/ujjwalkar0/Stores-Sales-Prediction/tree/main/Notebook
Website: https://github.com/ujjwalkar0/Stores-Sales-Prediction-Website