Package mvpa :: Package clfs :: Module kernel :: Class KernelMatern_3_2

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# Class KernelMatern_3_2

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The Matern kernel class for the case ni=3/2 or ni=5/2.

Note that it can handle a length scale for each dimension for Automtic Relevance Determination.

Instance Methods | [hide private]

__init__(self, length_scale=1.0, sigma_f=1.0, numerator=3.0, **kwargs) Initialize a Squared Exponential kernel instance. | source code

__repr__(self) repr(x) | source code

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

gradient(self, data1, data2) Compute gradient of the kernel matrix. A must for fast model selection with high-dimensional data. | source code

set_hyperparameters(self, hyperparameter) Set hyperaparmeters from a vector. | source code

Inherited from `Kernel`: `compute_gradient`, `compute_lml_gradient`, `compute_lml_gradient_logscale`, `reset` Inherited from `object`: `__delattr__`, `__format__`, `__getattribute__`, `__hash__`, `__new__`, `__reduce__`, `__reduce_ex__`, `__setattr__`, `__sizeof__`, `__str__`, `__subclasshook__`

Properties | [hide private]

Inherited from `object`: `__class__`

Method Details | [hide private]

### __init__(self, length_scale=1.0, sigma_f=1.0, numerator=3.0, **kwargs)
(Constructor)

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Initialize a Squared Exponential kernel instance.

Parameters:
  - `length_scale` (float OR numpy.ndarray) - the characteristic length-scale (or length-scales) of the phenomenon under investigation. (Defaults to 1.0)
  - `sigma_f` (float) - Signal standard deviation. (Defaults to 1.0)
  - `numerator`, `float` - the numerator of parameter ni of Matern covariance functions. Currently only numerator=3.0 and numerator=5.0 are implemented. (Defaults to 3.0)
Overrides: object.__init__

### __repr__(self)
(Representation operator)

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repr(x)

Overrides: object.__repr__
  (inherited documentation)

### compute(self, data1, data2=None)

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Compute kernel matrix.

Parameters:
  - `data1` (numpy.ndarray) - data
  - `data2` (numpy.ndarray) - data (Defaults to None)
Overrides: Kernel.compute

### set_hyperparameters(self, hyperparameter)

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Set hyperaparmeters from a vector.

Used by model selection. Note: 'numerator' is not considered as an hyperparameter.