Questions
- You are working as a data scientist for a pharmaceutical company. You are collaborating with other teammates to create a machine learning model to classify certain types of diseases on image exams. The company wants to prioritize the assertiveness rate of positive cases, even if they have to wrongly return false negatives. Which type of metric would you use to optimize the underlying model?
a. Recall
b. Precision
c. R-squared
d. RMSE
Answer
In this scenario, the company prefers to have a higher probability to be right on positive outcomes at the cost of wrongly classifying some positive cases as negative. Technically, they prefer to increase precision at the cost of reducing recall.
- You are working as a data scientist for a pharmaceutical company. You are collaborating with other teammates to create a machine learning model to classify certain types of diseases on image exams. The company wants to prioritize the capture of positive cases, even if they have to wrongly return...