The project explores the relationship between different symptoms and whether the patients tested positive for Covid-19. The dataset they use was released by the Israeli Ministry of Health and contains 7,651,053 observations with 10 different variables. The project objective is to create a model that can accurately predict if a person will test positive for the virus.
Things I like:
You have implemented different models and you have clearly explained how you chose them. I like that you took into consideration the false positive and false negative rates when you measured the accuracy of the model. Also, you tested the models with different hyperparameters.
I like that you have analyzed the difference between the Covid-19 and Influenza symptoms.
The part about WMD and fairness is also well written. You have given suggestions on how to prevent the model from being harmful.
Areas for Improvement:
Does the dataset contain information for patients only from Israel? Do you think that people living in other areas, under different conditions, might have different symptoms? Also, you might have to take into account the different living environments when comparing the Israeli patients with patients from West Virginia.
You can add more information about how you chose the hyperparameters of the models, what the optimal hyperparameters were, how they compare with the parameters from the previous models. Is there a significant difference between the parameters of your best model and the parameters of the other models?
You can also add more details on fixing the imbalanced dataset. Can that affect your predictions?
The project explores the relationship between different symptoms and whether the patients tested positive for Covid-19. The dataset they use was released by the Israeli Ministry of Health and contains 7,651,053 observations with 10 different variables. The project objective is to create a model that can accurately predict if a person will test positive for the virus.
Things I like:
Areas for Improvement:
Overall great job!