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Linear SVM decision boundary after a linear transformation of data

Let $w$ be the decision boundary of a linear SVM trained on the dataset $D=\{(x_i, y_i)_{i=1}^N\}$. Suppose we apply a linear transformation A to examples $x_i$s and obtain a new dataset $D'=\{(z_i, ...
emrea's user avatar
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Show that solution for the maximum margin hyperplane is unchanged when w.x + b = (+/-) 1 is replaced by arbitrary constant $\gamma$?

How to show that solution for the maximum margin hyperplane for hard-margin SVM is unchanged when w.x + b = (+/-) 1 is replaced by arbitrary constant $\gamma$? In the derivation for the SVM, we ...
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Does gradient descent for linear regression selects the minimal norm solution?

I was told that Gradient Descent finds the weights of smallest norm. This is what I understood in the linear regression setting: $f_w(x)=w^\top x$ are the linear functions $ \mathbb{R}^n \rightarrow \...
rod's user avatar
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