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Prediction of wine quality using machine learning techniques

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URI
http://hdl.handle.net/20.500.14044/30328
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  • Bánki közlemények [136]
Abstract
Climate change has affected every sector of nature, especially healthcare in recent years. These changes have affected the vineyards but also the characteristics of the wine. In this research project, two natural factors were taken into account, temperature and annual precipitation. At times when machine learning had not yet been discovered, each process was very complicated and time-consuming. Therefore, machine learning is a very smart move to get fast and accurate results.Pearson correlation coefficient was used to come to a conclusion.
Title
Prediction of wine quality using machine learning techniques
Author
Gjeka, Erestina
xmlui.dri2xhtml.METS-1.0.item-date-issued
2024-10
xmlui.dri2xhtml.METS-1.0.item-rights-access
Open access
xmlui.dri2xhtml.METS-1.0.item-identifier-issn
2560-2810
xmlui.dri2xhtml.METS-1.0.item-language
en
xmlui.dri2xhtml.METS-1.0.item-format-page
6 p.
xmlui.dri2xhtml.METS-1.0.item-subject-oszkar
Temperature, Precipitation, Wine, Pearson correlation coefficient
xmlui.dri2xhtml.METS-1.0.item-description-version
Kiadói változat
xmlui.dri2xhtml.METS-1.0.item-other-containerTitle
Bánki Közlemények
xmlui.dri2xhtml.METS-1.0.item-other-containerPeriodicalYear
2024
xmlui.dri2xhtml.METS-1.0.item-other-containerPeriodicalVolume
6. évf.
xmlui.dri2xhtml.METS-1.0.item-other-containerPeriodicalNumber
2. sz.
xmlui.dri2xhtml.METS-1.0.item-type-type
Tudományos cikk
xmlui.dri2xhtml.METS-1.0.item-subject-area
Műszaki tudományok - multidiszciplináris műszaki tudományok
xmlui.dri2xhtml.METS-1.0.item-publisher-university
Óbudai Egyetem
xmlui.dri2xhtml.METS-1.0.item-publisher-faculty
Bánki Donát Gépész és Biztonságtechnikai Mérnöki Kar

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