INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
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.
"Phone Price Prediction Using ML", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 12, page no.b247-b252, December-2023, Available :http://www.ijnrd.org/papers/IJNRD2312144.pdf
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2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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