Forecasting Laptop Prices: A Comparative Study of Machine Learning Algorithms for Predictive Modeling

Abstract

This paper describes a supervised machine learning-based laptop price prediction system. The machine learning prediction method used in the study is multiple linear regression, which provided an 81% prediction precision. Multiple linear regression employs multiple independent variables but only one dependent variable, the actual and predicted values of which are compared to determine precision of results. This paper proposes a system in which price is a predicted dependent variable derived from factors such as laptop model, RAM, ROM (HDD/SSD), GPU, CPU, IPS Display, and Touch Screen.

Keywords: Supervised machine learning, laptop, price prediction, multiple linear regression, independent variables, dependent variable, prediction precision, laptop model, RAM, ROM, HDD, SSD, GPU, CPU, IPS display, touch screen

JEL Classification: O3