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PyMVPA: Python MultiVariate Pattern Analysis
Package mvpa :: Package measures :: Module base :: Class BoostedClassifierSensitivityAnalyzer
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Class BoostedClassifierSensitivityAnalyzer

source code

Set sensitivity analyzers to be merged into a single output
Nested Classes [hide private]

Inherited from misc.state.ClassWithCollections: __metaclass__

Instance Methods [hide private]
 
__init__(self, clf, analyzer=None, combined_analyzer=None, slave_kwargs={}, **kwargs)
Initialize Sensitivity Analyzer for BoostedClassifier		 source code
 
untrain(self)
Untrain BoostedClassifierSensitivityAnalyzer		 source code
 
_call(self, dataset)
Computes a per-feature-measure on a given Dataset.		 source code

Inherited from Sensitivity: __call__, __repr__, feature_ids

Inherited from Sensitivity (private): _setClassifier

Inherited from FeaturewiseDatasetMeasure: combiner

Inherited from FeaturewiseDatasetMeasure (private): _postcall

Inherited from DatasetMeasure: null_dist, transformer

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

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

Class Variables [hide private]
  combined_analyzer = property(fget= lambda x: x.__combined_anal...

Inherited from Sensitivity: clf

Inherited from Sensitivity (private): _LEGAL_CLFS

Inherited from FeaturewiseDatasetMeasure: base_sensitivities

Inherited from DatasetMeasure: __doc__, null_prob, null_t, raw_results

Inherited from misc.state.ClassWithCollections: _DEV__doc__, descr

Instance Variables [hide private]
  __combined_analyzer
Combined analyzer to use
  __analyzer
Analyzer to use for basic classifiers within boosted classifier

Inherited from Sensitivity (private): _force_training

Properties [hide private]

Inherited from object: __class__

Method Details [hide private]

__init__(self, clf, analyzer=None, combined_analyzer=None, slave_kwargs={}, **kwargs)
(Constructor)

source code 
Initialize Sensitivity Analyzer for BoostedClassifier
Parameters:
  • clf (BoostedClassifier) - Classifier to be used
  • analyzer (analyzer) - Is used to populate combined_analyzer
  • slave_* - Arguments to pass to created analyzer if analyzer is None
Decorators:
  • @group_kwargs(prefixes= ['slave_'], assign= True)
Overrides: object.__init__

untrain(self)

source code 
Untrain BoostedClassifierSensitivityAnalyzer
Overrides: DatasetMeasure.untrain

_call(self, dataset)

source code 

Computes a per-feature-measure on a given Dataset.

Behaves like a DatasetMeasure, but computes and returns a 1d ndarray with one value per feature.

Overrides: DatasetMeasure._call
(inherited documentation)

Class Variable Details [hide private]

combined_analyzer

Value:
property(fget= lambda x: x.__combined_analyzer)

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PyMVPA: Python MultiVariate Pattern Analysis
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