Why do we prefer Logistic Regression over Linear Regression in the classification problems?

1. The predicted values are much more interpretable as they lie in the range of 0 to 1.
2. The Logit curve fits the data better than a straight line.
3. There is no assumption on the independence of predictor variables in the case of Logistic Regression.

a. (1) & (3)

b. (2) & (3)

c. (1) & (2)

d. All of the statements made are reasons for preferring Logistic Regression over Linear Regression