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Support Vector Machines
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Support Vector Machines
Support Vector Machines
[a-c] The figure below shows a small dataset with two classes (circles and rectangles). The red dotted line indicates the decision boundary we found using a support vector machine. We assume two-dimensional Euclidean space, where the point that two thick lines are crossing is the origin. For example, A is in (-3, 1), and the data point 6 is in 2,0). (a) List all support vectors? (b) Suppose we have an additional square class data point F at (1,0). When we learn an SVM including this data point, will the decision boundary be the same? (Please answer Yes or No). (C) Suppose we have an additional circle class data point 8 at (1,0). When we learn an SVM including this data point, will the decision boundary be the same? (Please answer Yes or No).
[a-c] The figure below shows a small dataset with two classes (circles and rectangles). The red dotted line indicates the decision boundary we found using a support vector machine. We assume two-dimensional Euclidean space, where the point that two thick lines are crossing is the origin. For example, A is in (-3, 1), and the data point 6 is in 2,0). (a) List all support vectors? (b) Suppose we have an additional square class data point F at (1,0). When we learn an SVM including this data point, will the decision boundary be the same? (Please answer Yes or No). (C) Suppose we have an additional circle class data point 8 at (1,0). When we learn an SVM including this data point, will the decision boundary be the same? (Please answer Yes or No).
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