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mvpa.clfs.glmnetΒΆ
GLM-Net (GLMNET) regression and 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 .. |
| Dataset(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes. |
| GLMNETWeights(clf, **kwargs[, force_train]) | SensitivityAnalyzer that reports the weights GLMNET trained |
| GLMNET_C(**kwargs) | GLM-NET Multinomial Classifier. |
| GLMNET_R(**kwargs) | GLM-NET Gaussian Regression Classifier. |
| Parameter(default, **kwargs[, ro, index, ...]) | This class shall serve as a representation of a parameter. |
| 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 .. |
| Dataset(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes. |
| GLMNETWeights(clf, **kwargs[, force_train]) | SensitivityAnalyzer that reports the weights GLMNET trained |
| GLMNET_C(**kwargs) | GLM-NET Multinomial Classifier. |
| GLMNET_R(**kwargs) | GLM-NET Gaussian Regression Classifier. |
| Parameter(default, **kwargs[, ro, index, ...]) | This class shall serve as a representation of a parameter. |
| Sensitivity(clf, **kwargs[, force_train]) | Sensitivities of features for a given Classifier. |
