Package mvpa :: Package clfs :: Module kernel :: Class Kernel
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Class Kernel

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Kernel function base class.
Instance Methods [hide private]
 
__init__(self)
x.__init__(...) initializes x; see x.__class__.__doc__ for signature
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__repr__(self)
repr(x)
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euclidean_distance(self, data1, data2=None, weight=None, symmetric=False)
Compute weighted euclidean distance matrix between two datasets.
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Inherited from object: __delattr__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __setattr__, __str__

Properties [hide private]

Inherited from object: __class__

Method Details [hide private]

__init__(self)
(Constructor)

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x.__init__(...) initializes x; see x.__class__.__doc__ for signature
Overrides: object.__init__
(inherited documentation)

__repr__(self)
(Representation operator)

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repr(x)
Overrides: object.__repr__
(inherited documentation)

euclidean_distance(self, data1, data2=None, weight=None, symmetric=False)

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Compute weighted euclidean distance matrix between two datasets.
Parameters:
  • data1 (numpy.ndarray) - first dataset
  • data2 (numpy.ndarray) - second dataset. If None set symmetric to True. (Defaults to None)
  • weight (numpy.ndarray) - vector of weights, each one associated to each dimension of the dataset (Defaults to None)
  • symmetric (bool) - compute the euclidean distance between the first dataset versus itself (True) or the second one (False). Note that (Defaults to False)