For the case: Improving Lead Generation at Eureka Forbes Using Machine Learning Algorithms 1. According to the case, what challenge(s) is/are Eureka Forbes facing? What is/are the marketing objectives of Kashif?

2. The dataset was randomly split into an 80:20 ratio for training and testing. A logistic regression model resulted in the following Confusion Matrix for the consumers in the test subset (obtained by using a 0.5 classification cutoff for the predicted probability): a. What is the True Positive Rate (TPR)? What is the False Positive Rate (FPR)?

b. What is the accuracy of classifications (i.e., what proportion of the consumers are correctly classified as converters and non-converters)?

c. What would be the accuracy of our classifications if all consumers were classified as non-converters?

Confusion Matrix	Classification
Actual		Class0	Class1
Class0	100685	40615
Class1 (converted)	204	362