Modelo Hedônico para Estimação do Valor de Imóveis: Aplicação em Nova Friburgo-RJ

Marco André Abud Kappel; Leonardo de Almeida Teodoro

doi:10.14295/vetor.v30i1.12879

Authors

Marco André Abud Kappel CEFET/RJ https://orcid.org/0000-0002-2004-7557
Leonardo de Almeida Teodoro CEFET/RJ https://orcid.org/0000-0001-6826-2558

DOI:

https://doi.org/10.14295/vetor.v30i1.12879

Keywords:

Machine Learning, Multi-linear Regression, Real Estate Price Prediction

Abstract

With the expansion of the real estate market in the mountainous region of Rio de Janeiro State, an increasing number of people need to deal with real estate purchasing and sale. However, to fair evaluate, a real estate unit is not a simple task and can be influenced by different characteristics. To assist in this task, the present work's objective is to identify the most critical attributes for evaluating a property and build a simple mathematical model that can be used to estimate the value of the property in this region. Data from properties for sale in the city of Nova Friburgo were extracted from online ad portals to build a unique database of real estate data. In these data, variable selection techniques and a multiple linear regression process were applied to obtain a mathematical model that describes prices based on the property's essential characteristics. The obtained results revealed that the most crucial aspect of the evaluation is the property's total area. The developed model could also predict prices with a mean percentage deviation of approximately 25% on the test database.

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