Lisbon´s Real Estate Analysis based on Proximity Calculations
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2023 |
| Tipo de documento: | Dissertação |
| Idioma: | eng |
| Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
| Texto Completo: | http://hdl.handle.net/10362/152094 |
Resumo: | Project Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics |
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Lisbon´s Real Estate Analysis based on Proximity CalculationsLisbonSmart CityReal EstateAccessibilityMobilitySDG 11 - Sustainable cities and communitiesProject Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business AnalyticsThe real estate market is always changing and evolving and with sustainability becoming an increasingly important topic, the way the price of a property is determined, and the factors taken in consideration, should evolve as well. Inspired by the popular concept of Smart Cities, more specifically the 15-minute city approach, which is a concept highly focused on accessibility and walkability in cities, different variables were calculated to assess each property’s accessibility and diversity of amenities. Both these factors are different for each property, depending on their location. This work presents an analysis of the real estate market in Lisbon where, aside from the physical attributes of a habitation, the diversity and accessibility to difference services in each location will be evaluated and integrated in the machine learning process. The goal is to know the impact of each calculated measure when predicting the price per meter value of each house, in order to help understand why similar houses across Lisbon have such distinctive prices. Both the Euclidean Distance and the Network Distance were used in the calculations. The distance to Tejo River and the number of commercial establishments within a 15-minute walk radius were two of the most important features in the predictive models tested. Three different methods were tested and improved, electing the Random Forest Regressor as the best the one and the one to be used in the final model. The final model had half of the variance in the target explained by the all the calculated features, which makes this analysis a potential good tool to help fill the gap of a predictive model that only factors in the physical characteristics of a house.Neto, Miguel de Castro Simões FerreiraJardim, João Bruno Morais de SousaRUNValério, Maria Madalena Jorge do Nascimento2023-04-24T13:49:12Z2023-04-102023-04-10T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/152094TID:203268385enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:34:27Zoai:run.unl.pt:10362/152094Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:54:47.636880Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
| dc.title.none.fl_str_mv |
Lisbon´s Real Estate Analysis based on Proximity Calculations |
| title |
Lisbon´s Real Estate Analysis based on Proximity Calculations |
| spellingShingle |
Lisbon´s Real Estate Analysis based on Proximity Calculations Valério, Maria Madalena Jorge do Nascimento Lisbon Smart City Real Estate Accessibility Mobility SDG 11 - Sustainable cities and communities |
| title_short |
Lisbon´s Real Estate Analysis based on Proximity Calculations |
| title_full |
Lisbon´s Real Estate Analysis based on Proximity Calculations |
| title_fullStr |
Lisbon´s Real Estate Analysis based on Proximity Calculations |
| title_full_unstemmed |
Lisbon´s Real Estate Analysis based on Proximity Calculations |
| title_sort |
Lisbon´s Real Estate Analysis based on Proximity Calculations |
| author |
Valério, Maria Madalena Jorge do Nascimento |
| author_facet |
Valério, Maria Madalena Jorge do Nascimento |
| author_role |
author |
| dc.contributor.none.fl_str_mv |
Neto, Miguel de Castro Simões Ferreira Jardim, João Bruno Morais de Sousa RUN |
| dc.contributor.author.fl_str_mv |
Valério, Maria Madalena Jorge do Nascimento |
| dc.subject.por.fl_str_mv |
Lisbon Smart City Real Estate Accessibility Mobility SDG 11 - Sustainable cities and communities |
| topic |
Lisbon Smart City Real Estate Accessibility Mobility SDG 11 - Sustainable cities and communities |
| description |
Project Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics |
| publishDate |
2023 |
| dc.date.none.fl_str_mv |
2023-04-24T13:49:12Z 2023-04-10 2023-04-10T00:00:00Z |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/masterThesis |
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masterThesis |
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publishedVersion |
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http://hdl.handle.net/10362/152094 TID:203268385 |
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http://hdl.handle.net/10362/152094 |
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TID:203268385 |
| dc.language.iso.fl_str_mv |
eng |
| language |
eng |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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