Prediction of wine quality using machine learning techniques

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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