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mvpa2.clfs.glmnetΒΆ
GLM-Net (GLMNET) regression and classifier.
Functions
| Rrx2(self, x) | Access delegator for R function [[ |
| accepts_dataset_as_samples(fx) | Decorator to extract samples from Datasets. |
Classes
| Classifier([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[, 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[, ro, index, value, name, doc]) | This class shall serve as a representation of a parameter. |
| Sensitivity(clf[, force_train]) | Sensitivities of features for a given Classifier. |
Exceptions
| Classifier([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[, 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[, ro, index, value, name, doc]) | This class shall serve as a representation of a parameter. |
| Sensitivity(clf[, force_train]) | Sensitivities of features for a given Classifier. |
