1. Repositório Aberto da Universidade do Porto
  2. FEUP - Faculdade de Engenharia
  3. FEUP - Dissertação
Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/134180
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dc.creatorNuno Miguel de Barbosa Ferreira
dc.date.accessioned2025-11-05T00:02:30Z-
dc.date.available2025-11-05T00:02:30Z-
dc.date.issued2021-03-29
dc.date.submitted2021-06-16
dc.identifier.othersigarra:474760
dc.identifier.urihttps://hdl.handle.net/10216/134180-
dc.descriptionIn management and administrative situations the need for planning is great and very valuable. Forecasting is a tool that aims to provide aid in decision making processes and efficient planning, whether that means learning from past mistakes, decreasing costs, better resource management amongst many other uses. When the data that's being analyzed is ordered over time then it's considered a time-series and its forecasting will try to estimate how that sequence of observations will behave in the future. Since time-series have specific traits it's interesting to convert time-series problems to regression ones. This thesis aims to automatically convert a time-series framework to a state-of-the-art regression framework and compare the two, trying to understand the advantages and disadvantages of the two approaches.
dc.language.isoeng
dc.rightsrestrictedAccess
dc.subjectEngenharia electrotécnica, electrónica e informática
dc.subjectElectrical engineering, Electronic engineering, Information engineering
dc.titleTime series vs regression, which is the best approach?
dc.typeDissertação
dc.contributor.uportoFaculdade de Engenharia
dc.identifier.doi10.34626/5hfx-tc95
dc.identifier.tid202824160
dc.subject.fosCiências da engenharia e tecnologias::Engenharia electrotécnica, electrónica e informática
dc.subject.fosEngineering and technology::Electrical engineering, Electronic engineering, Information engineering
thesis.degree.disciplineMestrado Integrado em Engenharia Electrotécnica e de Computadores
thesis.degree.grantorFaculdade de Engenharia
thesis.degree.grantorUniversidade do Porto
thesis.degree.level1
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