Predicting Mobile Prices with Machine Learning Techniques

• Published in: 2024 International Conference on Computational Intelligence and Computing Applications (ICCICA) Vol. 1; pp. 248 - 252
• Main Authors: Rana, Deepak Singh, Dhondiyal, Shiv Ashish, Singh, Sumeshwar, Kukreti, Sanjeev, Dhyani, Ashish
• Format: Conference Proceeding
• Language: English
• Published: IEEE 23-05-2024
• Subjects: Costs; Decision Tree; Machine learning; Machine learning algorithms; Phone Price Prediction; Prediction algorithms; Predictive models; Pricing; Support vector machines; SVM Method
• DOI: 10.1109/ICCICA60014.2024.10585222

Smartphones are increasingly vital to people on a daily basis. Telephones are utilized in all aspects of life, ranging from personal to professional, due to technological advancements. It serves a function beyond making phone calls. It enables internet connectivity and email reading. when not using the computer. The characteristics of a mobile phone are a crucial consideration when buying one.The overall objective of this research is to find the best way to apply machine learning to estimate the retail pricing of smartphones based on their individual specs. Individuals who frequently use their phone are more attentive to selecting features. When purchasing a cell phone, a comparison is done based on the price-performance ratio. Phone features are regarded as performance. This research aims to forecast if mobile phones with certain features are considered economical or expensive.This work is capable of being utilized in various marketing and business contexts to assist in making informed purchasing decisions by maximizing features while minimizing costs.