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Supervised Learning 1. The goal of Support Vector Machine is to fine a hyperplane, i.e., a decision boundary that linearly separates the points into different
Supervised Learning
1. The goal of Support Vector Machine is to fine a hyperplane, i.e., a decision boundary that linearly separates the points into different classes.
Given the hyperplane defined by y = x1 - 2x2.
i. How do you find the projection of a point , to the specified hyperplane?
ii. What are the distances of the following points from the hyperplane
x = [-1,2]
x = [1,0]
x = [1,1]
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