Predictive modelling applied to propensity to buy personal accidents insurance products

Detalhes bibliográficos
Autor(a) principal: Santos, Esdras Christo Moura dos
Data de Publicação: 2018
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/37698
Resumo: Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
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spelling Predictive modelling applied to propensity to buy personal accidents insurance productsPredictive modelsData miningSupervised learningPropensity to buyLogistic regressionDecision treesArtificial neural networksEnsemble modelsInternship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced AnalyticsPredictive models have been largely used in organizational scenarios with the increasing popularity of machine learning. They play a fundamental role in the support of customer acquisition in marketing campaigns. This report describes the development of a propensity to buy model for personal accident insurance products. The entire process from business understanding to the deployment of the final model is analyzed with the objective of linking the theory to practice.Castelli, MauroRUNSantos, Esdras Christo Moura dos2018-05-23T16:42:16Z2018-05-222018-05-22T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/37698TID:201919710enginfo: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:RCAAP2024-03-11T04:21:00Zoai:run.unl.pt:10362/37698Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:30:55.875016Repositório 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 Predictive modelling applied to propensity to buy personal accidents insurance products
title Predictive modelling applied to propensity to buy personal accidents insurance products
spellingShingle Predictive modelling applied to propensity to buy personal accidents insurance products
Santos, Esdras Christo Moura dos
Predictive models
Data mining
Supervised learning
Propensity to buy
Logistic regression
Decision trees
Artificial neural networks
Ensemble models
title_short Predictive modelling applied to propensity to buy personal accidents insurance products
title_full Predictive modelling applied to propensity to buy personal accidents insurance products
title_fullStr Predictive modelling applied to propensity to buy personal accidents insurance products
title_full_unstemmed Predictive modelling applied to propensity to buy personal accidents insurance products
title_sort Predictive modelling applied to propensity to buy personal accidents insurance products
author Santos, Esdras Christo Moura dos
author_facet Santos, Esdras Christo Moura dos
author_role author
dc.contributor.none.fl_str_mv Castelli, Mauro
RUN
dc.contributor.author.fl_str_mv Santos, Esdras Christo Moura dos
dc.subject.por.fl_str_mv Predictive models
Data mining
Supervised learning
Propensity to buy
Logistic regression
Decision trees
Artificial neural networks
Ensemble models
topic Predictive models
Data mining
Supervised learning
Propensity to buy
Logistic regression
Decision trees
Artificial neural networks
Ensemble models
description Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
publishDate 2018
dc.date.none.fl_str_mv 2018-05-23T16:42:16Z
2018-05-22
2018-05-22T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/37698
TID:201919710
url http://hdl.handle.net/10362/37698
identifier_str_mv TID:201919710
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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