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Questions about Support Vector Machines. SVMs are supervised learning models used for classification and regression tasks.
5
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What algorithm do SVMs use to minimize their objective function?
Support Vector Machines turn machine learning linear classification tasks into a linear optimization problems.
$$ \text{minimize } J(\theta,\theta_0) = \frac1n \sum_1^n \text{HingeLoss}(\theta,\theta_ …
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SVMs - Fat (Margin) Boundary: Why is $\max\frac1{||\theta||}=\min \frac{ ||\theta||^2}{2}$?
I am trying to understand SVMs in depth watching lectures from MIT.
The professor to reduces the classification problem into an optimization problem. To do that, he first defines the decision and marg …