Questions

a$)$ Taking into consideration the

i$)$ model; ii$)$ objective function; and iii$)$ optimization algorithm, discuss the differences between linear classifiers implemented using linear regression and logistic regression.

b$)$ How does the nature of linear regression as a predictive modeling technique influence its suitability for classification tasks, and why might it not be appropriate to apply linear regression in such scenarios?

c$)$ Describe the logistic regression equation and its components, including the sigmoid function.

d$)$ Using lecture slides, what fundamental elements characterize the training procedure in logistic regression, and how do these elements contribute to enhancing the model's efficacy?