A Study on Impact of Feature Selection on Product Valuation

摘要

E-commerce is emerging as the most favored retail destination. As more and more people are connecting to internet, the sales and revenue of online markets are increasing rapidly. In order to encourage more people to shop online e-commerce platforms set attracting offers on their products, offers which a common brick and mortar owner can never think off. To sell products in such low rates and also earn profits, online markets use machine learning algorithms to analyze their sales transactions and build better algorithms to predict prices and offers. In this paper transactional data is analyzed to discover features which influence offer value of products and then use different regression algorithms to predict better offer value for products.