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Suppose you have the following training set, and fit a logistic regression classifier .
Does adding polynomial features (e.g., instead using could increase how well we can fit the training data?
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For logistic regression, the gradient is given by ∂∂θjJ(θ)=1m∑mi=1(hθ(x(i))−y(i))x(i)j. Which of these is a correct gradient descent update for logistic regression with a learning rate of α?
Suppose you have the following training set, and fit a logistic regression classifier .
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