Q1: Linear model for regression Consider a linear-regression model with n=1 and m=3 with (X,Y) pairs as shown in the table above, what is w1E(W) (the gradient of MSE with respect to w1 ), when w0=0 and w1=1 ? Q2: Linear model for classification (perceptron) A. What is the value of w0,w1,w2 if you perform the perceptron algorithm on the following training set when the initial weight of w={0,1,1}, Iterations =2, activation function = sign, threshold =0,=1 B. Draw the decision boundary using the estimated weight. Q3: Linear Model for classification (logistic regression) 1. Suppose you have trained a logistic regression classifier for cancer prediction (cancer is the positive class) given the cell size (x1), and the best estimated parameters are w0=0.2,w1= 0.1 . What is the probability that a patient cell is cancerous if the cell size (x1)=3.5 centimeters