mvpa2.kernels.sg.LinearSGKernel

Inheritance diagram of LinearSGKernel
class mvpa2.kernels.sg.LinearSGKernel(normalizer_cls=None, normalizer_args=None, **kwargs)

A basic linear kernel computed via Shogun: K(a,b) = a*b.T

Attributes

descr Description of the object if any

Methods

add_conversion(typename, methodfull, methodraw) Adds methods to the Kernel class for new conversions
as_ls(kernel)
as_np() Converts this kernel to a Numpy-based representation
as_raw_ls(kernel)
as_raw_np() Directly return this kernel as a numpy array
as_raw_sg()
as_sg()
cleanup() Wipe out internal representation
compute(ds1[, ds2]) Generic computation of any kernel
computed(\*args, \*\*kwargs) Compute kernel and return self
reset()
Parameters:

normalizer_cls : sg.Kernel.CKernelNormalizer

Class to use as a normalizer for the kernel. Will be instantiated upon compute(). Only supported for shogun >= 0.6.5. By default (if left None) assigns IdentityKernelNormalizer to assure no normalization.

normalizer_args : None or list

If necessary, provide a list of arguments for the normalizer.

Attributes

descr Description of the object if any

Methods

add_conversion(typename, methodfull, methodraw) Adds methods to the Kernel class for new conversions
as_ls(kernel)
as_np() Converts this kernel to a Numpy-based representation
as_raw_ls(kernel)
as_raw_np() Directly return this kernel as a numpy array
as_raw_sg()
as_sg()
cleanup() Wipe out internal representation
compute(ds1[, ds2]) Generic computation of any kernel
computed(\*args, \*\*kwargs) Compute kernel and return self
reset()