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Predictive Analysis for Big Mart Sales Using Machine Learning Algorithms
- Source :
- 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS).
- Publication Year :
- 2021
- Publisher :
- IEEE, 2021.
-
Abstract
- Currently, supermarket run-centres, Big Marts keep track of each individual item's sales data in order to anticipate potential consumer demand and update inventory management. Anomalies and general trends are often discovered by mining the data warehouse's data store. For retailers like Big Mart, the resulting data can be used to forecast future sales volume using various machine learning techniques like big mart. A predictive model was developed using Xgboost, Linear regression, Polynomial regression, and Ridge regression techniques for forecasting the sales of a business such as Big-Mart, and it was discovered that the model outperforms existing models.
- Subjects :
- Polynomial regression
Computer science
business.industry
Consumer demand
05 social sciences
Volume (computing)
InformationSystems_DATABASEMANAGEMENT
02 engineering and technology
Machine learning
computer.software_genre
Data warehouse
Regression
Data store
Order (business)
0502 economics and business
Linear regression
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Artificial intelligence
business
computer
050203 business & management
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS)
- Accession number :
- edsair.doi...........6e94d56e2020c28d84d5eacdb070701f