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Package mvpa :: Package featsel :: Module base :: Class FeatureSelection

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Class FeatureSelection

Base class for any feature selection

Base class for Functors which implement feature selection on the datasets.

Nested Classes

Inherited from misc.state.ClassWithCollections: __metaclass__

Instance Methods

__init__(self, **kwargs)
x.__init__(...) initializes x; see help(type(x)) for signature

source code

__call__(self, dataset, testdataset=None)
Invocation of the feature selection

source code

untrain(self)
'Untrain' feature selection

source code

Inherited from misc.state.ClassWithCollections: __getattribute__, __new__, __repr__, __setattr__, __str__, reset

Inherited from object: __delattr__, __format__, __hash__, __reduce__, __reduce_ex__, __sizeof__, __subclasshook__

Class Variables

selected_ids = StateVariable(enabled= False)

Inherited from misc.state.ClassWithCollections: _DEV__doc__, descr

Properties

Inherited from object: __class__

Method Details

init(self, **kwargs)
(Constructor)

x.__init__(...) initializes x; see help(type(x)) for signature

Overrides: object.__init__: (inherited documentation)

call(self, dataset, testdataset=None)
(Call operator)

Invocation of the feature selection

Returns a tuple with the dataset containing the selected features. If present the tuple also contains the selected features of the test dataset. Derived classes must provide interface to access other relevant to the feature selection process information (e.g. mask, elimination step (in RFE), etc)

Parameters:

dataset (Dataset) - dataset used to select features
testdataset (Dataset) - dataset the might be used to compute a stopping criterion

untrain(self)

'Untrain' feature selection

Necessary for full 'untraining' of the classifiers. By default does nothing, needs to be overridden in corresponding feature selections to pass to the sensitivities

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