Question 1
Milo’s Evaluation (ME) is a loan default prediction company that uses manual workforce to suggest possible defaulters. Dr. Milo, the Chief Data Officer of ME, has decided to replace the manual workforce with a cutting-edge Logistic Regression Model that takes “Age” and “Income” as parameters to predict defaulters. The model is configured such that a “Defaulter” is categorised as the positive class. The final model had the parameters as specified in Table-1 below. To test the model, the data in Table-2 is used as test data. Given this information, answer the given subquestions.
At a threshold of 0.8, how many “True Positives” is the model predicting?