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Multivariate Pattern Analysis in Python |
Feature selection base class and related stuff base classes and helpers.
The comprehensive API documentation for this module, including all technical details, is available in the Epydoc-generated API reference for mvpa.featsel.base (for developers).
Bases: mvpa.misc.state.ClassWithCollections
Base class for any feature selection
Base class for Functors which implement feature selection on the datasets.
See also
Derived classes might provide additional methods via their base classes. Please refer to the list of base classes (if it exists) at the begining of the FeatureSelection documentation.
Full API documentation of FeatureSelection in module mvpa.featsel.base.
Bases: mvpa.featsel.base.FeatureSelection
Feature elimination through the list of FeatureSelection’s.
Given as list of FeatureSelections it applies them in turn.
Initialize feature selection pipeline
Parameters: |
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See also
Derived classes might provide additional methods via their base classes. Please refer to the list of base classes (if it exists) at the begining of the FeatureSelectionPipeline documentation.
Full API documentation of FeatureSelectionPipeline in module mvpa.featsel.base.
Bases: mvpa.featsel.base.FeatureSelection
Feature elimination.
A FeaturewiseDatasetMeasure is used to compute sensitivity maps given a certain dataset. These sensitivity maps are in turn used to discard unimportant features.
Initialize feature selection
Parameters: |
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See also
Derived classes might provide additional methods via their base classes. Please refer to the list of base classes (if it exists) at the begining of the SensitivityBasedFeatureSelection documentation.
Full API documentation of SensitivityBasedFeatureSelection in module mvpa.featsel.base.