Covid 19 is a dangerous virus which has taken the lives of many innocent people all over the world. Most of the deaths are caused because of the patient unable to identify the presence of virus in their body due to which it becomes too late to react and get treatment as soon as possible, which ultimately resulted as casualties. This project will help to detect and identify whether the virus is present in the human body with the help of symptoms in the early stage and they can recover from it.
We have applied two types of clustering algorithms, K-means and BIRCH to our Covid-19 dataset.
Our dataset contained 27 columns and 3,16,800 rows. The columns contained binary values representing the presence of various symptoms such as dry cough, diarrhea, fever, sore throat, difficulty in breathing, nasal congestion, tiredness as well as other characteristics of the patient such as their gender, whether they were in contact with other Covid-19 positive individuals as well as their country of residence.
The following are the seven primary variables that will influence whether or not someone has coronavirus disease, with descriptions of each variable: Country: List of countries visited by the individual. Age: According to WHO Age Group Standard, each person's age group is classified. Symptoms: Fever, tiredness, breathing difficulty, dry cough, and sore throat are the five prominent symptoms of COVID-19, according to the WHO. Any additional symptoms such as Diarrhea, Pains, Nasal Congestion, Runny Nose, and Other Severity: The severity degree, Moderate, Mild Severe Has the person made touch with any other COVID-19 patients?