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PyMVPA: Python MultiVariate Pattern Analysis
Package mvpa :: Package clfs :: Package libsvmc :: Module sens :: Class LinearSVMWeights
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Class LinearSVMWeights

source code

SensitivityAnalyzer for the LIBSVM implementation of a linear SVM.
Nested Classes [hide private]

Inherited from misc.state.ClassWithCollections: __metaclass__

Instance Methods [hide private]
 
__init__(self, clf, **kwargs)
Initialize the analyzer with the classifier it shall use.		 source code
 
_call(self, dataset, callables=[])
Computes a per-feature-measure on a given Dataset.		 source code

Inherited from measures.base.Sensitivity: __call__, __repr__, feature_ids, untrain

Inherited from measures.base.Sensitivity (private): _setClassifier

Inherited from measures.base.FeaturewiseDatasetMeasure: combiner

Inherited from measures.base.FeaturewiseDatasetMeasure (private): _postcall

Inherited from measures.base.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]
  _ATTRIBUTE_COLLECTIONS = ['params']
  biases = StateVariable(enabled= True, doc= "Offsets of separat...
  split_weights = Parameter(False, allowedtype= 'bool', doc= "If...
  _customizeDocInherit = True

Inherited from measures.base.Sensitivity: clf

Inherited from measures.base.Sensitivity (private): _LEGAL_CLFS

Inherited from measures.base.FeaturewiseDatasetMeasure: base_sensitivities

Inherited from measures.base.DatasetMeasure: __doc__, null_prob, null_t, raw_results

Inherited from misc.state.ClassWithCollections: _DEV__doc__, descr

Instance Variables [hide private]

Inherited from measures.base.Sensitivity (private): _force_training

Properties [hide private]

Inherited from object: __class__

Method Details [hide private]

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

source code 
Initialize the analyzer with the classifier it shall use.
Parameters:
  • clf, LinearSVM - classifier to use. Only classifiers sub-classed from LinearSVM may be used.
Overrides: object.__init__

_call(self, dataset, callables=[])

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: measures.base.DatasetMeasure._call
(inherited documentation)

Class Variable Details [hide private]

biases

Value:
StateVariable(enabled= True, doc= "Offsets of separating hyperplanes")

split_weights

Value:
Parameter(False, allowedtype= 'bool', doc= "If binary classification e\
ither to sum SVs per each " "class separately")

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PyMVPA: Python MultiVariate Pattern Analysis
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