"Machine Learning-Based Price Classification for Used Electronic Devices"
تفاصيل العمل
In the rapidly growing market for used electronic devices, determining the fair price of a device can be challenging due to its numerous influencing factors. This project leverages machine learning to classify used devices into three price categories—low, medium, and high—based on features like brand, specifications, and condition. Using a dataset of 3,454 entries with 15 features, we preprocess and analyze the data to build a predictive model. A K–Nearest Neighbors (KNN) algorithm is employed, achieving an impressive test accuracy of 81.87%. The results provide valuable insights for pricing strategies, inventory management, and customer targeting in the used device market.
مهارات العمل
بطاقة العمل
طلب عمل مماثل
