Suppose that we want to build a SVM classifier that classifies two-dimensional data (i.e., X = [x1, x2]) into two classe

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Suppose That We Want To Build A Svm Classifier That Classifies Two Dimensional Data I E X X1 X2 Into Two Classe 1 (60.86 KiB) Viewed 41 times

Suppose that we want to build a SVM classifier that classifies two-dimensional data (i.e., X = [x1, x2]) into two classes: diamonds and crosses. We have a set of training data that is plotted as follows: □ X2 900 X1 Explain how you would build the SVM classifier with respect to the classification problem provided by providing detailed explanations for the followings: i. The support vector optimization function used to classify the two different classes. Is there a need to use a kernel function to solve the problem? Why? And which kernel is most suitable? Explain. (8 marks) ii. The concept of large margin classifier with regards to SVM and the problem presented. (2 marks) iii. What is the C parameter in SVM, and how will it affect the final classification result for the given problem? (3 marks)