2. Suppose you have the following training set, and fit a logistic regression cl

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2. Suppose you have the following training set, and fit a logistic regression classifier ho(z) = g@s + + 2x2) 0.5 1.5 2 1.5 0.5 Which of the following are true? Check all that apply Adding polynomial features (e.g., instead using (z) g(80 + 1 z 1 + 2T2 + 3zf + 4 z 1 z2 + 5z ) ) could increase how well we can fit the training data At the optimal value of (e.g., found by fminunc), we will have J(820 Adding polynomial features (e.g., instead using because we are now summing over more terms. If we train gradient descent for enough iterations, for some examples ) in the training set it is possible to obtain ho(0)) > 1

Explanation / Answer

2- A,B

3 -A,B

4 - A,B

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