Home

Trees

Indices

Help

Package mvpa :: Package measures :: Module base :: Class ProxyClassifierSensitivityAnalyzer

[frames] | no frames]

Class ProxyClassifierSensitivityAnalyzer

Set sensitivity analyzer output just to pass through

Nested Classes

Inherited from misc.state.ClassWithCollections: __metaclass__

Instance Methods

__init__(self, clf, analyzer=None, **kwargs)
Initialize Sensitivity Analyzer for BoostedClassifier

source code

untrain(self)
Untrain corresponding classifier for Sensitivity

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

clf_sensitivities = StateVariable(enabled= False, doc= "Stores...

analyzer = property(fget= lambda x: x.__analyzer)

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

__analyzer
Analyzer to use for basic classifiers within boosted classifier

Inherited from Sensitivity (private): _force_training

Properties

Inherited from object: __class__

Method Details

init(self, clf, analyzer=None, **kwargs)
(Constructor)

Initialize Sensitivity Analyzer for BoostedClassifier

Parameters:

combiner - The combiner is only applied if the computed featurewise dataset measure is more than one-dimensional. This is different from a transformer, which is always applied. By default, the sum of absolute values along the second axis is computed.

Decorators:

@group_kwargs(prefixes= ['slave_'], assign= True)

Overrides: object.__init__

untrain(self)

Untrain corresponding classifier for Sensitivity

Overrides: DatasetMeasure.untrain: (inherited documentation)

_call(self, dataset)

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

clf_sensitivities

Value:

StateVariable(enabled= False, doc= "Stores sensitivities of the proxie
d classifier")

Home

Trees

Indices

Help