mvpa2.clfs.plrΒΆ
Penalized logistic regression classifier.
Functions
| accepts_dataset_as_samples(fx) | Decorator to extract samples from Datasets. |
| asobjarray(x) | Generates numpy.ndarray with dtype object from an iterable Is needed to assure object dtype, so first empty array of dtype=object needs to be constructed and then only items to be assigned. |
Classes
| Classifier([space]) | Abstract classifier class to be inherited by all classifiers .. |
| ConditionalAttribute([enabled]) | Simple container intended to conditionally store the value .. |
| Dataset(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes. |
| PLR([lm, criterion, reduced, maxiter]) | Penalized logistic regression Classifier. |
| PLRWeights(clf[, force_train]) | Sensitivity reporting linear weights of PLR |
| Sensitivity(clf[, force_train]) | Sensitivities of features for a given Classifier. |
Exceptions
| Classifier([space]) | Abstract classifier class to be inherited by all classifiers .. |
| ConditionalAttribute([enabled]) | Simple container intended to conditionally store the value .. |
| Dataset(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes. |
| PLR([lm, criterion, reduced, maxiter]) | Penalized logistic regression Classifier. |
| PLRWeights(clf[, force_train]) | Sensitivity reporting linear weights of PLR |
| Sensitivity(clf[, force_train]) | Sensitivities of features for a given Classifier. |
