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Consider the following loss function for training pair (X,y): L = max{0, a - y(W X)}The test instances are predicted as y = sign{W X}.
Consider the following loss function for training pair (X,y): L = max{0, a - y(W X)}The test instances are predicted as y = sign{W X}. A value of a = 0 corresponds to the perceptron criterion and a value of a = 1 corresponds to the SVM. Show that any value of a > 0 leads to the SVM with an unchanged optimal solution when no regularization is used. What happens when regularization is used?
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Design Operation And Evaluation Of Mobile Communications
Authors: Gavriel Salvendy ,June Wei
1st Edition
3030770249, 978-3030770242
