Question: 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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