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mvpa.kernels.sgΒΆ
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
| CustomSGKernel(kernel_cls, **kwargs[, ...]) | Class which can wrap any Shogun kernel and it’s kernel parameters |
| Kernel(*args, **kwargs) | Abstract class which calculates a kernel function between datasets |
| LinearSGKernel(**kwargs[, normalizer_cls, ...]) | A basic linear kernel computed via Shogun: K(a,b) = a*b.T |
| Parameter(default, **kwargs[, ro, index, ...]) | This class shall serve as a representation of a parameter. |
| PolySGKernel(**kwargs) | Polynomial kernel: K(a,b) = (a*b.T + c)**degree |
| PrecomputedSGKernel(**kwargs[, 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) |
| RealFeatures(*args) | The class SimpleFeatures implements dense feature matrices. |
| SGKernel(*args, **kwargs) | A Kernel object with internal representation in Shogun |
