we studied the logistic regression problem with binary label ybi {0, 1}. In this exercise, we will perform a different procedure to formulate the logistic regression problem with a modified label ybi {1, +1}.] A data scientist is given N samples (xbi , ybi) with xbi being a d-dimensional vector and ybi {1, +1}. The data scientist supposes that nature generates the label following the Bernoulli distribution with ybi = ( +1 with probability ( truexbi), 1 with probability 1 ( truexbi), where true is a d-dimensional vector containing the true (but unknown) parameters that we wish to recover. (a) [2pt] Write (z) as a function of (z)