COVID-19 Prediction based on Symptoms
COVID-19 Prediction based on Symptoms
Embedded Files
Via Random Forest model
Via Random Forest model
Covid Detection model
Covid Detection model
I have created an ML model which can predict if a person has covid or not using symptoms they have. It is a supervised Classification model (Random forest model) developed using python. The model has a 96.7% Accuracy.
About COVID-19
About COVID-19
>> From WHO website
>> From WHO website
Coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. Most people infected with the virus will experience mild to moderate respiratory illness and recover without requiring special treatment. However, some will become seriously ill and require medical attention. Older people and those with underlying medical conditions like cardiovascular disease, diabetes, chronic respiratory disease, or cancer are more likely to develop serious illness. Anyone can get sick with COVID-19 and become seriously ill or die at any age.
Classification model
Classification model
Classification was done using logistic regression and Random forest and the following confusion matrix was obtained.
The Accuracy, Precision and recall along with F1 score were better for the random forest model, and so I went with it.
Python Scripts
Python Scripts
Random_forest.py
Random_forest.py
This python program creates the random forest model using the data.csv dataset and saves it as a joblib file.
Predictions.py
Predictions.py
This python program accepts user information and uses it to predict Covid 19 condition of the user using the created model.
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