The data used in this project will help to identify whether a person is going torecover from coronavirus symptomsor not based on some pre-defined standard symptoms. These symptoms are based on guidelines given by the World Health Organization (WHO).
This dataset has daily level information on the number of affected cases, deaths and recovery from 2019 novel coronavirus. Please note that this is a time series data and so the number of cases on any given day is the cumulative number.
The data is available from 22 Jan, 2020.Data is in “data.csv”.
The dataset contains 14major variables that will be having an impact on whether someone has recovered or not, the description of each variable are as follows,
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Country:where the person resides.
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Location:which part in the Country.
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Age: Classification of the age group for each person, based on WHO Age Group Standard.
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Gender:Male or Female.
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Visited_Wuhan: whether the personhas visited Wuhan, China or not.
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From_Wuhan:whether the personis fromWuhan, China or not.
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Symptoms:there are six families of symptoms that are coded in six fields.
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Time_before_symptoms_appear.
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Result: death (1) or recovered (0).
It is required to design different classifiersto the predict the outcome (death/recovered) when a new person is admitted to the hospital.The data is already cleaned and preprocessed.