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Recall that in lectures we showed that the Logistic Regression for binary classification boils down to solving the following optimization problem (training error) over n training samples: n T f(w) = Σlog (1 + e¯Yiw™; Xi -4:20-21) i=1 a) Compute the gradient of f(w). b) Please write the pseudocode for using GD to optimize the f(w). c) Argue that

Related Book For  answer-question

Statistics The Art and Science of Learning from Data

3rd edition

Authors: Alan Agresti, Christine A. Franklin

ISBN: 978-0321755940