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

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# Class FeatureSelection

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Base class for any feature selection

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

Nested Classes | [hide private]

Inherited from `misc.state.ClassWithCollections`: `__metaclass__`

Instance Methods | [hide private]

__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 | [hide private]

| selected_ids = `StateVariable(enabled= False)`
Inherited from `misc.state.ClassWithCollections`: `_DEV__doc__`, `descr`

Properties | [hide private]

Inherited from `object`: `__class__`

Method Details | [hide private]

### __init__(self, **kwargs)
(Constructor)

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

Overrides: object.__init__
  (inherited documentation)

### __call__(self, dataset, testdataset=None)
(Call operator)

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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)

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'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