3. SVM, see Figure 2 (1) If you remove the following any one red points from the data. Does the decision boundary will change? A. Yes B. No (2) If you remove the non-red circled points from the data, the decision boundary will change? A. True B. False (3) When the C parameter is set to innite, which of the following holds true? A. The optimal hyperplane if exists, will be the one that completely separates the data B. The soft-margin classier will separate the data C. None of the above (4) The e ectiveness of an SVM depends upon: A. Selection of Kernel B. Kernel Parameters C. Soft Margin Parameter C D. All of the above

3. SVM, see Figure 2 (1) If you remove the following any one red points from the data. Does the decision boundary will change? A. Yes B. No (2) If you remove the non-red circled points from the data, the decision boundary will change? A. True B. False (3) When the C parameter is set to infinite, which of the following holds true? A. The optimal hyperplane if exists, will be the one that completely separates the data B. The soft-margin classifier will separate the data C. None of the above (4) The effectiveness of an SVM depends upon: A. Selection of Kernel B. Kernel Parameters C. Soft Margin Parameter C D. All of the above Figure 2: Q3