| Class | Description |
|---|---|
| CachedKernel |
Base class for RBFKernel and PolyKernel that implements a simple LRU.
|
| CheckKernel |
Class for examining the capabilities and finding problems with kernels.
|
| Kernel |
Abstract kernel.
|
| KernelEvaluation |
Class for evaluating Kernels.
|
| NormalizedPolyKernel |
The normalized polynomial kernel.
K(x,y) = <x,y>/sqrt(<x,x><y,y>) where <x,y> = PolyKernel(x,y) Valid options are: |
| PolyKernel |
The polynomial kernel : K(x, y) = <x, y>^p or
K(x, y) = (<x, y>+1)^p
Valid options are:
|
| PrecomputedKernelMatrixKernel |
This kernel is based on a static kernel matrix that
is read from a file.
|
| Puk |
The Pearson VII function-based universal kernel.
For more information see: B. |
| RBFKernel |
The RBF kernel : K(x, y) = exp(-gamma*(x-y)^2)
Valid options are: |
| RegOptimizer |
Base class implementation for learning algorithm of SMOreg
Valid options are:
|
| RegSMO |
Implementation of SMO for support vector regression
as described in :
A.J. |
| RegSMOImproved |
Learn SVM for regression using SMO with Shevade,
Keerthi, et al.
|
| SMOset |
Stores a set of integer of a given size.
|
| StringKernel |
Implementation of the subsequence kernel (SSK) as
described in [1] and of the subsequence kernel with lambda pruning (SSK-LP)
as described in [2].
For more information, see Huma Lodhi, Craig Saunders, John Shawe-Taylor, Nello Cristianini, Christopher J. |