Analytical Methods of Machine Learning Model for E-Commerce Sales Analysis and Prediction
- Title
- Analytical Methods of Machine Learning Model for E-Commerce Sales Analysis and Prediction
- Creator
- Anushka Xavier K.; Manjunath C.; Manohar M.; Gurudas V.R.; Jayapandian N.; Balamurugan M.
- Description
- In the commercial market, E-commerce sales show a significant trend and have attracted many consumers. Ecommerce sales forecasting has a significant role in an organization's growth and aids in improved operation. Many studies have been conducted in the past using statistical, fundamental, and data mining techniques for better analysis and prediction of sales. However, the current scenario calls for a better study that combines the available information to propose different machine-learning techniques. The sole motive of the study is to analyze and determine different machine learning models to predict accurate results. The research observed that the Extreme Gradient Boosting model outperformed all other models and brought a good result. It produced an RMSE value of 0.0004 and Explained Variance score of 0.99. Decision Tree algorithm also shows an exemplary result. 2023 IEEE.
- Source
- Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications
- Date
- 2023-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Boosting; Explained Variance; Extreme Gradient Boosting; Machine Learning; Sales Prediction
- Coverage
- Anushka Xavier K., CHRIST (Deemed to Be University), Department of CSE, Bangalore, India; Manjunath C., CHRIST (Deemed to Be University), Department of CSE, Bangalore, India; Manohar M., CHRIST (Deemed to Be University), Department of CSE, Bangalore, India; Gurudas V.R., CHRIST (Deemed to Be University), Department of CSE, Bangalore, India; Jayapandian N., CHRIST (Deemed to Be University), Department of CSE, Bangalore, India; Balamurugan M., CHRIST (Deemed to Be University), Department of CSE, Bangalore, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835033577-4
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Anushka Xavier K.; Manjunath C.; Manohar M.; Gurudas V.R.; Jayapandian N.; Balamurugan M., “Analytical Methods of Machine Learning Model for E-Commerce Sales Analysis and Prediction,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 27, 2025, https://archives.christuniversity.in/items/show/19829.