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Predictive Analytics for Real Estate Valuation: A Random Forest Approach for High-Precision Rental Price Estimation in Indian Metropolitans

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Predictive Analytics for Real Estate Valuation: A Random Forest Approach for High-Precision Rental Price Estimation in Indian Metropolitans


Rohit Uddhar



Rohit Uddhar "Predictive Analytics for Real Estate Valuation: A Random Forest Approach for High-Precision Rental Price Estimation in Indian Metropolitans" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications, March 2026, pp.373-390, URL: https://www.ijtsrd.com/papers/ijtsrd101630.pdf

The global real estate market, particularly within the rapidly urbanizing corridors of India, has long been characterized by extreme information asymmetry and a lack of pricing transparency. For the average home-seeker or small-scale investor, determining the "fair market value" of a rental property is often an exercise in guesswork which depends on broker evaluations and current market conditions. This research addresses these systemic inefficiencies by proposing and implementing an intelligent data-driven framework for real estate valuation which connects advanced machine learning concepts with user learning needs. The framework includes a strong predictive system which operates through Random Forest Regression technology. The Random Forest algorithm provides an effective solution for urban housing challenges because it can understand the complex relationships between property features and local geographical patterns which include square footage and BHK configuration. Our model was developed using a complete data collection that included various Indian metropolitan areas and it went through an extensive preprocessing procedure which involved converting "Furnishing" and "City" data into categorical formats and creating a special "Luxury Score" assessment tool. This score measures the total effect of secondary facilities which include balconies and bathrooms to help the model differentiate between standard and premium listings with accurate statistical results. The research introduces a new method for prediction which replaces static prediction methods with dynamic simulation techniques. Users frequently encounter "what-if" scenarios so we created an AI-driven Feature Simulator. Users can change property features through this tool which provides interactive property variable manipulation.

Real Estate Valuation, Random Forest Regression, Indian Housing Market, Predictive Analytics, Interactive Simulation.


IJTSRD101630
Special Issue | Smart Innovations in Computer Science and Applications, March 2026
373-390
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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