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PyMVPA: Python MultiVariate Pattern Analysis
Package mvpa :: Package featsel :: Module base :: Class SensitivityBasedFeatureSelection
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Class SensitivityBasedFeatureSelection

source code

Feature elimination.

A FeaturewiseDatasetMeasure is used to compute sensitivity maps given a certain dataset. These sensitivity maps are in turn used to discard unimportant features.



Nested Classes [hide private]

Inherited from misc.state.ClassWithCollections: __metaclass__

Instance Methods [hide private]
 
__init__(self, sensitivity_analyzer, feature_selector=FractionTailSelector(0.05), **kwargs)
Initialize feature selection		 source code
 
__call__(self, dataset, testdataset=None)
Select the most important features		 source code

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

Inherited from object: __delattr__, __hash__, __reduce__, __reduce_ex__

Class Variables [hide private]
  sensitivity = StateVariable(enabled= False)
  sensitivity_analyzer = property(fget= lambda self: self.__sens...

Inherited from FeatureSelection: selected_ids

Inherited from misc.state.ClassWithCollections: _DEV__doc__, descr

Instance Variables [hide private]
  __sensitivity_analyzer
Sensitivity analyzer to use once
  __feature_selector
Functor which takes care about removing some features.
Properties [hide private]

Inherited from object: __class__

Method Details [hide private]

__init__(self, sensitivity_analyzer, feature_selector=FractionTailSelector(0.05), **kwargs)
(Constructor)

source code 
Initialize feature selection
Parameters:
  • sensitivity_analyzer (FeaturewiseDatasetMeasure) - sensitivity analyzer to come up with sensitivity
  • feature_selector (Functor) - Given a sensitivity map it has to return the ids of those features that should be kept.
Overrides: FeatureSelection.__init__

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

source code 

Select the most important features

Returns a tuple of two new datasets with selected feature subset of dataset.

Parameters:
  • dataset (Dataset) - used to compute sensitivity maps
  • testdataset, Dataset - optional dataset to select features on
Overrides: FeatureSelection.__call__

Class Variable Details [hide private]

sensitivity_analyzer

Value:
property(fget= lambda self: self.__sensitivity_analyzer, doc= "Measure\
 which was used to do selection")

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PyMVPA: Python MultiVariate Pattern Analysis
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