Research Article
Television Price Prediction Based on Features with Machine Learning
@INPROCEEDINGS{10.1007/978-3-031-35078-8_42, author={Marumoju Dheeraj and Manan Pathak and G. R. Anil and Mohamed Sirajudeen Yoosuf}, title={Television Price Prediction Based on Features with Machine Learning}, proceedings={Intelligent Systems and Machine Learning. First EAI International Conference, ICISML 2022, Hyderabad, India, December 16-17, 2022, Proceedings, Part I}, proceedings_a={ICISML}, year={2023}, month={7}, keywords={Machine Learning Price Prediction TV Price Web Scraping ECommerce}, doi={10.1007/978-3-031-35078-8_42} }- Marumoju Dheeraj
Manan Pathak
G. R. Anil
Mohamed Sirajudeen Yoosuf
Year: 2023
Television Price Prediction Based on Features with Machine Learning
ICISML
Springer
DOI: 10.1007/978-3-031-35078-8_42
Abstract
Television is both a source of information and a means of communication, and it plays an important role in everyone's life. It broadcasts news, documentaries, sporting events, and other events, among other things. In the market, different models of televisions having different features are available based on the user requirement. This paper tries to develop a model that can offer a client with a fair pricing estimate based on a tradeoff between features and price. A four-step process is devised for this objective, which includes real-time data scraping from an eCommerce website and creation of a model using machine learning algorithms. The algorithms like Multi Linear Regression, SVM (Regressor), Decision Tree Regressor are used for price prediction. Decision Tree Regression was found to be more accurate in predicting television prices in this study.
