You are training a 2-way classifier using the logisitc loss. The training set has three training samples: (21, 1), (2, 1), (23, -1), where an E Rd, n = 1,2,3, and their class labels are 1, 1, and -1, respectively. During training, we store and view the prediction results (output of the Sigmoid function) after a certain iteration. 0.6 Y1 = 10.7 0.4 1. (1 point) On this training set (with 3 samples), compute the classification accuracy. Briefly write down your steps. 2. (2 points) Does the classification model converge after this iteration? Explain your answer in 3 sentences. 3. (2 points) In a few sentences explain why logistic regression is superior to linear regression for the classification