Question: Question (2): b- For a multi-class SVM case, three categories are given with the following score functions:-S1(X) = x1 - x2 + 2x3 + 0.1,

Question (2): b- For a multi-class SVM case, three categories are

Question (2): b- For a multi-class SVM case, three categories are given with the following score functions:-S1(X) = x1 - x2 + 2x3 + 0.1, S2(X) =-X1 + x2 - 2x3 +10, and S3(X) = X1 - X2+ 2x3 -0.1. A data set of 10 labelled feature vectors are given below:- X1 X2 X3 Label 180 12 177 9 195 125 181 173 30 87 8 25 112 203 114 192 167 127 149 71 210 242 48 165 70 41 245 57 2 3 2 2 3 1 3 3 2 2 (0) (ii) Find the total loss considering a MCSVM classification approach. Find the total probability of error considering a Bayesian classification approach

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