This content refers to an unreleased development version of PyMVPA
To provide the most recent news and documentation www.pymvpa.org reflects the
development 0.6 series of PyMVPA. If you are interested in the
documentation of the previous stable 0.4 series of PyMVPA, please
visit v04.pymvpa.org.
mvpa.clfs.enetΒΆ
Elastic-Net (ENET) regression classifier.
Functions
| accepts_dataset_as_samples(fx) | Decorator to extract samples from Datasets. |
Classes
| Classifier(**kwargs[, space]) | Abstract classifier class to be inherited by all classifiers .. |
| ENET(**kwargs[, lm, trace, normalize, ...]) | Elastic-Net regression (ENET) Classifier. |
| ENETWeights(clf, **kwargs[, force_train]) | SensitivityAnalyzer that reports the weights ENET trained |
| Sensitivity(clf, **kwargs[, force_train]) | Sensitivities of features for a given Classifier. |
Exceptions
| Classifier(**kwargs[, space]) | Abstract classifier class to be inherited by all classifiers .. |
| ENET(**kwargs[, lm, trace, normalize, ...]) | Elastic-Net regression (ENET) Classifier. |
| ENETWeights(clf, **kwargs[, force_train]) | SensitivityAnalyzer that reports the weights ENET trained |
| Sensitivity(clf, **kwargs[, force_train]) | Sensitivities of features for a given Classifier. |
