The Advanced Feature-Driven Smartphone Price Prediction Using Machine Learning

Abstract

A rapid growth occurred in the smart phone industry owing to the launch of numerous fresh devices across various price categories. It is advantageous to both the device makers and the users to be aware of the relative price of a smartphone which is in relation to its specifications. This research focuses on artificial intelligence for the purpose of making predictions on the price ranges of the devices with some specific attributes such as:- Fingerprint Sensor, storage space, 5G Support, Water Resistance and Number of Sims , Face Lock. The last one is rather significant, as in some regions of the world devices fitted with one or two SIM cards or more are likely to be used most because of the different wide range of connectivity they offer. This methodology includes cleansing, transformation of data and applying suitable techniques from the machine learning. The developed model is precise and accurateand the output information of the model suffices a good number of questions that assist companies on how to set prices and also shape their clients’ buying behaviors.