PyMVPA shogun-based kernels
Provides interface to kernels defined in shogun toolbox. Commonly used kernels are provided with convenience classes: LinearSGKernel, RbfSGKernel, PolySGKernel. If you need to use some other shogun kernel, use CustomSGKernel to define one.
Functions
exists(dep[, force, raise_, issueWarning]) | Test whether a known dependency is installed on the system. |
Classes
Bogus | |
CustomSGKernel(kernel_cls[, kernel_params]) | Class which can wrap any Shogun kernel and it’s kernel parameters .. |
Kernel(*args, **kwargs) | Abstract class which calculates a kernel function between datasets Each instance has an internal representation self._k which might be of a different form depending on the intended use. |
LinearSGKernel([normalizer_cls, normalizer_args]) | A basic linear kernel computed via Shogun: K(a,b) = a*b.T .. |
Parameter(default[, ro, index, value, name, doc]) | This class shall serve as a representation of a parameter. |
PolySGKernel(**kwargs) | Polynomial kernel: K(a,b) = (a*b.T + c)**degree c is 1 if and only if ‘inhomogenous’ is True .. |
PrecomputedSGKernel([matrix]) | A kernel which is precomputed from a numpy array or a Shogun kernel .. |
RbfSGKernel(**kwargs) | Radial basis function: K(a,b) = exp(-||a-b||**2/sigma) .. |
SGKernel(*args, **kwargs) | A Kernel object with internal representation in Shogun .. |