Hard-margin dual
Definition taught in Support vector machines, part of Statistical learning
Hard-margin dual
| Type | Definition |
| Taught in | Support vector machines |
| Part | Statistical learning |
\begin{aligned} \text{maximise}\quad Q(\alpha)&=\sum_{i=1}^{n}\alpha_i-\frac12\sum_{i=1}^{n}\sum_{j=1}^{n}\alpha_i\alpha_j y_i y_j x_i^\top x_j\\ \text{subject to}\quad \sum_{i=1}^{n}\alpha_i y_i&=0,\qquad \alpha_i\ge 0. \end{aligned}
Used in
- Taught in Support vector machines, where the derivation and examples are.
- All 10 questions on Support vector machines
See also
Signed distance · Vapnik’s radius–margin bound · Hard-margin primal · Soft-margin primal · Kernel · Linear separators and the margin · Distance to a hyperplane · Why maximise the margin?