Paper Title
Phone Price Prediction Using ML
Article Identifiers
: Authors
Keywords
preprocessing, machine learning, metrics, predict, specifications
Abstract
The market for mobile phones in india is highly competitive, with new models being introduced frequently. Consumers are always looking for the latest technology and features, and they are willing to pay a premium price for it. In this paper, we propose a machine learning-based approach to predict the price of mobile phones based on various features such as brand, model, screen type, camera quality, and battery life. A dataset of mobile phones is collected with their corresponding features and prices from various online retailers. The data is processed and then different machine learning algorithms are applied such as linear regression, decision trees, and random forests to predict the price of mobile phones. The performance of the algorithms is evaluated using metrics such as root mean squared error, R-squared value and mean absolute error. Finally, a model is selected based on the performance. The proposed system will help rural Indians in purchasing phones within their budget and with optimal specifications.
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How To Cite (APA)
G.Chamundeswari, K. Srihari Teja, Gorle Vasu, K.Uma Gayatri, & K.Vikas (December-2023). Phone Price Prediction Using ML. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(12), b247-b252. https://ijnrd.org/papers/IJNRD2312144.pdf
Issue
Volume 8 Issue 12, December-2023
Pages : b247-b252
Other Publication Details
Paper Reg. ID: IJNRD_210468
Published Paper Id: IJNRD2312144
Downloads: 000122257
Research Area: Computer Science & TechnologyÂ
Author Type: Indian Author
Country: ELURU, Andhra Pradesh, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2312144.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2312144
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