Kernel
Definition taught in Support vector machines, part of Statistical learning
Kernel
| Type | Definition |
| Taught in | Support vector machines |
| Part | Statistical learning |
| Questions using it | 6 |
A kernel is a function equivalent to an inner product in some feature space,
K(x_i,x_j)=\phi(x_i)^\top\phi(x_j).
The kernel trick replaces inner products in the feature space by K evaluated on the original points. The feature map is never computed.
Used in
- Taught in Support vector machines, where the derivation and examples are.
- Also used in Model selection for stochastic models · Statistical classifiers and discriminant analysis
- Questions that use it (6) — Kernel density by hand · A kernel is a density (answer) · A tempting wrong turn (answer) · Clustering and smoothing choices · A tempting wrong turn (answer) · Nonlinear separation of XOR
- All 10 questions on Support vector machines
See also
Kernel density estimator · Kernel of a density · Gaussian kernel · Kernel trick · Dual problem · Epanechnikov kernel · Gram matrix · Polynomial kernel