Decision Boundary Line (Linear/Non-Linear)

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The discussion centers on a non-linear decision boundary defined by the equation (1 + X1)^2 + (2 − X2)^2 = 4, which describes a circular shape. It is argued that while this boundary is non-linear in terms of the original variables X1 and X2, it can be transformed into a linear form by introducing quadratic terms, specifically X1^2 and X2^2. By rewriting the equation, it becomes evident that the relationship can be expressed linearly in the extended feature space. The transformation allows for a linear representation, demonstrating how non-linear boundaries can be managed through feature engineering. This highlights the importance of feature space manipulation in machine learning to address non-linearity.
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Homework Statement



Given a non-linear decision boundary line: (1 + X1)^2 + (2 − X2)^2 = 4

Argue that while the decision boundary is not linear in terms of X1 and X2, it is linear in terms of X1,X1^2 , X2, and X2^2 .

The Attempt at a Solution



I'm honestly not sure. I realize the curve is a circle, but I don't understand how it could be turned linear by having it terms of X1,X1^2 , X2, and X2^2
 
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Is it because we are extending the feature space by including quadratic terms that can address this non-linearity?
 
It's pretty basic algebra that (1+ X1)^2+ (2- X2)^2= X1^2- 2X1+ 1+ X2^2- 4X2+ 4= 4
so X1^2- 2X1+ X2^2- 4X2+ 1= 0.

If you let Y1= X1^2 and Y2= X2^2, then you have Y1- 2X1+ Y2- 4Y1+ 1= 0 which is 'linear in X1, X2, Y1, and Y2".
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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