Year: 2025
Type: article
Abstract: House Price Prediction is crucial for informed decision-making in real estate markets. The accurate prediction of house prices holds significant importance in real estate markets, facilitating informed decision making for stakeholders. This study focuses on the application of machine learning (ML) techniques to predict house prices in Mumbai, India, a city renowned for its dynamic real estate landscape. By delving into the intricacies of Mumbai's real estate data, this research aims to identify the most influential factors driving property values and determine the optimal ML models for prediction. The study underscores the significance of locational and structural attributes in shaping house prices, highlighting the complex interplay between market dynamics and property characteristics. Furthermore, it investigates the impact of socio-economic factors, infrastructure development, and neighborhood amenities on housing values. Findings from this research contribute to the understanding of Mumbai's real estate market dynamics and provide actionable insights for stakeholders, including homebuyers, sellers, and real estate developers.
Author: Vansh Talwar
Language: English
Topic: Housing Market and Economics
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7083012441
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