University of Bahrain
Scientific Journals

Machine Learning model to predict the number of cases contaminated by COVID-19

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dc.contributor.author Erraissi, Allae
dc.contributor.author Banane, Mouad
dc.date.accessioned 2020-07-21T09:51:22Z
dc.date.available 2020-07-21T09:51:22Z
dc.date.issued 2020-07-01
dc.identifier.issn 2210-142X
dc.identifier.uri https://journal.uob.edu.bh:443/handle/123456789/3994
dc.description.abstract This paper presents a dedicated machine learning model to predict the number of cases infected by the Corona Virus; the case of Morocco was chosen to validate this study. Completely realized in Spark ML with the 'Scala' language and tested for a certain number of algorithms generated on datasets coming from dedicated sources to gather Covid19 data in the world. The results show the possibility of achieving better scores prediction after using the proposed method. We tested our model on the case of China and the results were relevant. The proposed Machine Learning model can be applied to data from any country in the world. We have applied it in this paper to the case of Morocco and China. We are sending this work to the world to help them fight this 2019 Corona Virus pandemic. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/ *
dc.subject Machine Learning en_US
dc.subject Spark ML model en_US
dc.subject Artificial Intelligence model en_US
dc.subject coronavirus en_US
dc.subject predicting COVID-19 en_US
dc.title Machine Learning model to predict the number of cases contaminated by COVID-19 en_US
dc.type Article en_US
dc.identifier.doi http://dx.doi.org/10.12785/ijcds/100189
dc.volume 9 en_US
dc.pagestart 1 en_US
dc.pageend 11 en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US


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