Class SillySensitivityAnalyzer

Simple one which just returns xrange[-N/2, N/2], where N is the number of features

Nested Classes

Inherited from misc.state.ClassWithCollections: __metaclass__

Instance Methods

__init__(self, mult=1, **kwargs)
Initialize

source code

__call__(self, dataset)
Train linear SVM on dataset and extract weights from classifier. source code

Inherited from measures.base.FeaturewiseDatasetMeasure: __repr__, combiner

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

Inherited from measures.base.DatasetMeasure: null_dist, transformer, untrain

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

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

Class Variables

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

Properties

Inherited from object: __class__

Method Details

Initialize

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.

Overrides: object.__init__

(inherited documentation)

Train linear SVM on dataset and extract weights from classifier.

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