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Package mvpa :: Package clfs :: Module kernel :: Class KernelConstant

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Class KernelConstant

The constant kernel class.

Instance Methods

__init__(self, sigma_0=1.0, **kwargs)
Initialize the constant kernel instance.

source code

__repr__(self)
repr(x)

source code

compute(self, data1, data2=None)
Compute kernel matrix.

source code

set_hyperparameters(self, hyperparameter)

source code

compute_lml_gradient(self, alphaalphaT_Kinv, data)

source code

compute_lml_gradient_logscale(self, alphaalphaT_Kinv, data)

source code

Inherited from Kernel: compute_gradient, reset

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __setattr__, __sizeof__, __str__, __subclasshook__

Properties

Inherited from object: __class__

Method Details

init(self, sigma_0=1.0, **kwargs)
(Constructor)

Initialize the constant kernel instance.

Parameters:

sigma_0 (float) - standard deviation of the Gaussian prior probability N(0,sigma_0**2) of the intercept of the constant regression. (Defaults to 1.0)

Overrides: object.__init__

repr(self)
(Representation operator)

repr(x)

Overrides: object.__repr__: (inherited documentation)

compute(self, data1, data2=None)

Compute kernel matrix.

Parameters:

data1 (numpy.ndarray) - data
data2 (numpy.ndarray) - data (Defaults to None)

Overrides: Kernel.compute

compute_lml_gradient(self, alphaalphaT_Kinv, data)

Overrides: Kernel.compute_lml_gradient

compute_lml_gradient_logscale(self, alphaalphaT_Kinv, data)

Overrides: Kernel.compute_lml_gradient_logscale

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