Proceedings of the International Workshop on Advances in Deep Learning for Image Analysis and Computer Vision (IWADIC 2025)

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Using Machine Learning Methods to Predict Mobile Phone Prices

Authors
Wenbo Lu1, *
1Mathematical and Statistical Data Science, Faculty of Science, University of Technology Sydney, Sydney, New South Wales, Australia
*Corresponding author. Email: Wales-Australia-Wenbo.Lu@student.uts.edu.au
Corresponding Author
Wenbo Lu
Available Online 24 April 2026.
DOI
10.2991/978-94-6239-648-7_71How to use a DOI?
Keywords
Logistic Regression; Random Forest; MLP
Abstract

This study analyzes the price range and configurations of mobile phones on the market to help emerging mobile phone companies accurately position their product prices and better compete in the mobile phone market. The study uses machine learning techniques to predict mobile phone prices, employing three methods: logistic regression, random forest, and Multilayer Perceptron (MLP) to build models, and generating prediction accuracy and feature importance maps related to mobile phones for each model. Through comparison of model accuracy, this study found that the logistic regression model performed best, with the highest prediction rate. Analysis of the feature importance maps and exploratory analysis revealed that feature combinations have a more significant impact on pricing than single features. In addition, an important finding is that higher-priced mobile phones are less likely to support memory expansion. This study not only achieves price prediction but also provides an important reference for the research and development and marketing of electronic products.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Workshop on Advances in Deep Learning for Image Analysis and Computer Vision (IWADIC 2025)
Series
Advances in Computer Science Research
Publication Date
24 April 2026
ISBN
978-94-6239-648-7
ISSN
2352-538X
DOI
10.2991/978-94-6239-648-7_71How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Wenbo Lu
PY  - 2026
DA  - 2026/04/24
TI  - Using Machine Learning Methods to Predict Mobile Phone Prices
BT  - Proceedings of the International Workshop on Advances in Deep Learning for Image Analysis and Computer Vision (IWADIC 2025)
PB  - Atlantis Press
SP  - 652
EP  - 666
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-648-7_71
DO  - 10.2991/978-94-6239-648-7_71
ID  - Lu2026
ER  -