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

[hide private]
[frames] | no frames]

# Class ProxyClassifierSensitivityAnalyzer

source code

Set sensitivity analyzer output just to pass through

Nested Classes | [hide private]

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

Instance Methods | [hide private]

__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 | [hide private]

| 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 | [hide private]

| __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, **kwargs)
(Constructor)

source code

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)

source code

Untrain corresponding classifier for Sensitivity

Overrides: DatasetMeasure.untrain
  (inherited documentation)

### _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]

### clf_sensitivities

Value:

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