mvpa2.kernels.np.ConstantKernel

Inheritance diagram of ConstantKernel
class mvpa2.kernels.np.ConstantKernel(*args, **kwargs)

The constant kernel class.

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(kernel) Converts directly to a Shogun kernel
as_sg(kernel) Converts this kernel to a Shogun-based representation
cleanup() Wipe out internal representation
compute(ds1[, ds2]) Generic computation of any kernel
compute_lml_gradient(alphaalphaT_Kinv, data)
compute_lml_gradient_logscale(...)
computed(\*args, \*\*kwargs) Compute kernel and return self
reset()

Base Kernel class has no parameters

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(kernel) Converts directly to a Shogun kernel
as_sg(kernel) Converts this kernel to a Shogun-based representation
cleanup() Wipe out internal representation
compute(ds1[, ds2]) Generic computation of any kernel
compute_lml_gradient(alphaalphaT_Kinv, data)
compute_lml_gradient_logscale(...)
computed(\*args, \*\*kwargs) Compute kernel and return self
reset()
compute_lml_gradient(alphaalphaT_Kinv, data)
compute_lml_gradient_logscale(alphaalphaT_Kinv, data)