mvpa2.kernels.sg.PolySGKernel

class mvpa2.kernels.sg.PolySGKernel(**kwargs)

Polynomial kernel: K(a,b) = (a*b.T + c)**degree c is 1 if and only if ‘inhomogenous’ is True

Methods

add_conversion(typename, methodfull, methodraw)	Adds methods to the Kernel class for new conversions :Parameters: typename : string Describes kernel type methodfull : function Method which converts to the new kernel object class methodraw : function Method which returns a raw kernel ..
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 Assumptions: - ds1, ds2 are either datasets or arrays, - presumably 2D (not checked neither enforced here - _compute takes ndarrays.
computed(*args, **kwargs)	Compute kernel and return self
reset()

Initialize instance of PolySGKernel

Parameters:

degree :

Polynomial order of the kernel. (Default: 2)

inhomogenous :

Whether +1 is added within the expression. (Default: True)

use_normalization :

Optional normalization. (Default: False)

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.

Methods

add_conversion(typename, methodfull, methodraw)	Adds methods to the Kernel class for new conversions :Parameters: typename : string Describes kernel type methodfull : function Method which converts to the new kernel object class methodraw : function Method which returns a raw kernel ..
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 Assumptions: - ds1, ds2 are either datasets or arrays, - presumably 2D (not checked neither enforced here - _compute takes ndarrays.
computed(*args, **kwargs)	Compute kernel and return self
reset()