Open AccessUsing Supervised Machine Learning and Empirical Bayesian Kriging to Reveal Correlates and Patterns of COVID-19 Disease Outbreak in Sub-Saharan Africa: Exploratory Data Analysis
Author(s) -
Amobi Onovo,
Akinyemi Atobatele,
Abiye Kalaiwo,
Christopher Obanubi,
Ezekiel James,
Pamela Gado,
Gertrude Odezugo,
Dolapo Ogundehin,
Doreen Magaji,
Michele Russell
Publication year - 2020
Publication title -
ssrn electronic journal
Language(s) - English
Resource type - Journals
ISSN - 1556-5068
DOI - 10.2139/ssrn.3580721
Subject(s) - covid-19 , outbreak , bayesian probability , kriging , disease , exploratory data analysis , exploratory analysis , computer science , machine learning , artificial intelligence , econometrics , geography , statistics , data science , data mining , medicine , mathematics , infectious disease (medical specialty) , virology , pathology
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