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Support Vector Machine refers to "a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis."
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Why is SVM calculated in this way?
I have a question regarding SVM. … x_i=0 \rightarrow w =\sum_i \alpha_i y_i x_i$
Filling this in the Lagrange gives
$L(\alpha)=\frac{1}{2}\sum_i \sum_j \alpha_i \alpha_j y_i y_j x_i' x_j + \sum_i{\alpha_i}
$
But this is not how SVM …