Interpretable Machine Learning for Real Estate Valuation: A Case Study with Small Data

Autores
Gutiérrez, Emiliano; López del Río, Lorena Caridad; Caridad Ocerín, Jose María
Año de publicación
2025
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
This study explores residential property valuation in Seville, Spain, using interpretable machine learning techniques on a small dataset of 1701 sales ads of apartments collected online. Unlike conventional approaches that rely on large datasets, our research addresses the unique challenges of small data samples while maintaining model interpretability. We compare traditional hedonic linear regression with Random Forest algorithms. The results provide actionable insights for real estate stakeholders in medium-sized urban markets, bridging the gap between econometric tradition and machine learning innovation.
Instituto de Investigación en Informática
Materia
Ciencias Informáticas
interpretable machine learning
hedonic pricing
random forest
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-nd/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/182614
Acceder
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network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Interpretable Machine Learning for Real Estate Valuation: A Case Study with Small DataGutiérrez, EmilianoLópez del Río, Lorena CaridadCaridad Ocerín, Jose MaríaCiencias Informáticasinterpretable machine learninghedonic pricingrandom forestThis study explores residential property valuation in Seville, Spain, using interpretable machine learning techniques on a small dataset of 1701 sales ads of apartments collected online. Unlike conventional approaches that rely on large datasets, our research addresses the unique challenges of small data samples while maintaining model interpretability. We compare traditional hedonic linear regression with Random Forest algorithms. The results provide actionable insights for real estate stakeholders in medium-sized urban markets, bridging the gap between econometric tradition and machine learning innovation.Instituto de Investigación en Informática2025-06info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf101-105http://sedici.unlp.edu.ar/handle/10915/182614enginfo:eu-repo/semantics/altIdentifier/isbn/978-950-34-2583-1info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/4.0/Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T11:21:39Zoai:sedici.unlp.edu.ar:10915/182614Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 11:21:40.088SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Interpretable Machine Learning for Real Estate Valuation: A Case Study with Small Data
title Interpretable Machine Learning for Real Estate Valuation: A Case Study with Small Data
spellingShingle Interpretable Machine Learning for Real Estate Valuation: A Case Study with Small Data
Gutiérrez, Emiliano
Ciencias Informáticas
interpretable machine learning
hedonic pricing
random forest
title_short Interpretable Machine Learning for Real Estate Valuation: A Case Study with Small Data
title_full Interpretable Machine Learning for Real Estate Valuation: A Case Study with Small Data
title_fullStr Interpretable Machine Learning for Real Estate Valuation: A Case Study with Small Data
title_full_unstemmed Interpretable Machine Learning for Real Estate Valuation: A Case Study with Small Data
title_sort Interpretable Machine Learning for Real Estate Valuation: A Case Study with Small Data
dc.creator.none.fl_str_mv Gutiérrez, Emiliano
López del Río, Lorena Caridad
Caridad Ocerín, Jose María
author Gutiérrez, Emiliano
author_facet Gutiérrez, Emiliano
López del Río, Lorena Caridad
Caridad Ocerín, Jose María
author_role author
author2 López del Río, Lorena Caridad
Caridad Ocerín, Jose María
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
interpretable machine learning
hedonic pricing
random forest
topic Ciencias Informáticas
interpretable machine learning
hedonic pricing
random forest
dc.description.none.fl_txt_mv This study explores residential property valuation in Seville, Spain, using interpretable machine learning techniques on a small dataset of 1701 sales ads of apartments collected online. Unlike conventional approaches that rely on large datasets, our research addresses the unique challenges of small data samples while maintaining model interpretability. We compare traditional hedonic linear regression with Random Forest algorithms. The results provide actionable insights for real estate stakeholders in medium-sized urban markets, bridging the gap between econometric tradition and machine learning innovation.
Instituto de Investigación en Informática
description This study explores residential property valuation in Seville, Spain, using interpretable machine learning techniques on a small dataset of 1701 sales ads of apartments collected online. Unlike conventional approaches that rely on large datasets, our research addresses the unique challenges of small data samples while maintaining model interpretability. We compare traditional hedonic linear regression with Random Forest algorithms. The results provide actionable insights for real estate stakeholders in medium-sized urban markets, bridging the gap between econometric tradition and machine learning innovation.
publishDate 2025
dc.date.none.fl_str_mv 2025-06
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
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status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/182614
url http://sedici.unlp.edu.ar/handle/10915/182614
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-950-34-2583-1
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
dc.format.none.fl_str_mv application/pdf
101-105
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
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reponame_str SEDICI (UNLP)
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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