Question: Why do we prefer Logistic Regression over Linear Regression in the classification problems? The predicted values are much more interpretable as they lie in the

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

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