Assets Estimation of Domestic and Scalable Edifice using Machine Learning Approach

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  • Create Date 7 August, 2025
  • Last Updated 14 August, 2025

Authors : Mohini Barapatre , Akshata Bettawar, Ishita Dharmik, Barnabas Johnson, Ansar Sheikh

DOI : 10.46335/IJIES.2024.9.7.10

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Abstract— Property valuation is a crucial aspect of real estate investment and decision-making processes, encompassing both residential and commercial sectors. Traditional methods of property valuation often rely on subjective assessments, leading to potential inaccuracies and inconsistencies. This research paper investigates the efficacy of regression analysis as a quantitative tool for property valuation, focusing on residential and commercial buildings. Through a comparative study, various regression models are employed to analyze the relationship between property characteristics and market values, utilizing datasets encompassing a diverse range of properties. The findings of this research is to provide valuable insights into the applicability and accuracy of regression analysis in property valuation for both residential and commercial buildings. Moreover, the study contributes to the existing body of knowledge by highlighting the nuances and complexities involved in valuing properties across different segments of the real estate market. Ultimately, the outcomes of this research can inform stakeholders, including investors, developers, appraisers, and policymakers, in making informed decisions regarding property investments and market assessments