Advanced Machine Learning Techniques for Real Estate Price Prediction: A Comprehensive Review

DOI

10.2991/978-94-6463-738-0_75How to use a DOI?

Keywords

Housing price prediction; machine learning; neural networks; random forests; deep learning; joint self-attention mechanisms

Abstract

The difficulties of predicting home prices in real estate investing, economic forecasting, and urban planning are discussed in this paper. As machine learning (ML) has developed, more sophisticated techniques like neural networks, random forests, and deep learning models have overtaken more conventional methods like linear regression. This review analyzes the predictive performance and feature relevance of many machine learning approaches for predicting home prices. Methods such as self-attention processes, regression, and heterogeneous data processing are investigated. A cross-regional comparison demonstrates how applicable these models are in the actual world. The results highlight how crucial strong data integration and sophisticated analytics are to increasing forecast accuracy. Policymakers, investors, and urban planners all benefit from the insights this research offers on how to optimize housing market analysis.

Copyright

© 2025 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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TY  - CONF
AU  - Jyoti Rani
AU  - Shiv Kumar Verma
AU  - Lakshay Dhiman
AU  - Divyanshu Rawat
AU  - Sujal Kumar
AU  - Satvik Shekhar Sharma
PY  - 2025
DA  - 2025/06/22
TI  - Advanced Machine Learning Techniques for Real Estate Price Prediction: A Comprehensive Review
BT  - Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)
PB  - Atlantis Press
SP  - 959
EP  - 971
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-738-0_75
DO  - 10.2991/978-94-6463-738-0_75
ID  - Rani2025
ER  -