Machine Learning-Based Mobile Device Resale Price Estimator: A Predictive Analytics Approach - Umm-e-Laila Mehdi; Khalid Mahboob; Samar Raza Talpur; Khaliq Ahmed; Mohammad Khurram (JISR on Computing)
The rapid growth of Pakistan's mobile resale market, based on frequent gadget upgrades, requires smartphone valuations to be precise. This study introduces a mobile resale calculator that uses machine learning algorithms to provide predictions. Our technology analyzes the key parameters, which include storage capacity, facial recognition, PTA clearance, battery health, screen quality, warranty coverage, packaging, and device condition, to give accurate forecasts. The proposed approach allows for the making of informed decisions and maximization of returns on investment. Interestingly, our experiment shows that the Random Forest algorithm yields an accuracy of 0.97, which justifies our methodology.