Question: b- For a multi-class SVM one dimensional case, three categories are given with the following score functions:-S1(X) =W11X1 + W10, S2(X) = W21X1 + W20,

b- For a multi-class SVM one dimensional case, three categories are

b- For a multi-class SVM one dimensional case, three categories are given with the following score functions:-S1(X) =W11X1 + W10, S2(X) = W21X1 + W20, and S3(X) = W31X1 + W30. A data set of 10 labelled feature vectors are given below:- X1 1 10 25 20 40 60 55 60 70 90 Label 1 1 1 2 2 2 3 3 33 (i) Find the two threshold values in terms of the weighing coefficients that can be used to divide the space of x into three regions. Choose the best values for the weighting coefficients to classify those feature values into their correct classes using the MCSVM. (ii)

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