Application of machine learning techniques for solving real world business problems : the case study - target marketing of insurance policies

Detalhes bibliográficos
Autor(a) principal: Juozenaite, Ineta
Data de Publicação: 2018
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10362/32410
Resumo: Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
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spelling Application of machine learning techniques for solving real world business problems : the case study - target marketing of insurance policiesMachine LearningLogistic RegressionDecision Tree CARTArtificial Neural NetworkMultilayerPercptronBackpropagation learning algorithmSupport Vector MachineKernel GaussianProject Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceThe concept of machine learning has been around for decades, but now it is becoming more and more popular not only in the business, but everywhere else as well. It is because of increased amount of data, cheaper data storage, more powerful and affordable computational processing. The complexity of business environment leads companies to use data-driven decision making to work more efficiently. The most common machine learning methods, like Logistic Regression, Decision Tree, Artificial Neural Network and Support Vector Machine, with their applications are reviewed in this work. Insurance industry has one of the most competitive business environment and as a result, the use of machine learning techniques is growing in this industry. In this work, above mentioned machine learning methods are used to build predictive model for target marketing campaign of caravan insurance policies to achieve greater profitability. Information Gain and Chi-squared metrics, Regression Stepwise, R package “Boruta”, Spearman correlation analysis, distribution graphs by target variable, as well as basic statistics of all variables are used for feature selection. To solve this real-world business problem, the best final chosen predictive model is Multilayer Perceptron with backpropagation learning algorithm with 1 hidden layer and 12 hidden neurons.Castelli, MauroRUNJuozenaite, Ineta2018-03-13T16:26:59Z2018-03-092018-03-09T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/32410TID:201878038enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:31:23Zoai:run.unl.pt:10362/32410Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:02:26.087316Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Application of machine learning techniques for solving real world business problems : the case study - target marketing of insurance policies
title Application of machine learning techniques for solving real world business problems : the case study - target marketing of insurance policies
spellingShingle Application of machine learning techniques for solving real world business problems : the case study - target marketing of insurance policies
Juozenaite, Ineta
Machine Learning
Logistic Regression
Decision Tree CART
Artificial Neural Network
Multilayer
Percptron
Backpropagation learning algorithm
Support Vector Machine
Kernel Gaussian
title_short Application of machine learning techniques for solving real world business problems : the case study - target marketing of insurance policies
title_full Application of machine learning techniques for solving real world business problems : the case study - target marketing of insurance policies
title_fullStr Application of machine learning techniques for solving real world business problems : the case study - target marketing of insurance policies
title_full_unstemmed Application of machine learning techniques for solving real world business problems : the case study - target marketing of insurance policies
title_sort Application of machine learning techniques for solving real world business problems : the case study - target marketing of insurance policies
author Juozenaite, Ineta
author_facet Juozenaite, Ineta
author_role author
dc.contributor.none.fl_str_mv Castelli, Mauro
RUN
dc.contributor.author.fl_str_mv Juozenaite, Ineta
dc.subject.por.fl_str_mv Machine Learning
Logistic Regression
Decision Tree CART
Artificial Neural Network
Multilayer
Percptron
Backpropagation learning algorithm
Support Vector Machine
Kernel Gaussian
topic Machine Learning
Logistic Regression
Decision Tree CART
Artificial Neural Network
Multilayer
Percptron
Backpropagation learning algorithm
Support Vector Machine
Kernel Gaussian
description Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
publishDate 2018
dc.date.none.fl_str_mv 2018-03-13T16:26:59Z
2018-03-09
2018-03-09T00:00:00Z
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/10362/32410
TID:201878038
url http://hdl.handle.net/10362/32410
identifier_str_mv TID:201878038
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:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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