mvpa2.clfs.smlrΒΆ
Sparse Multinomial Logistic Regression classifier.
Functions
| accepts_dataset_as_samples(fx) | Decorator to extract samples from Datasets. |
| expand_contraint_spec(spec) | Helper to translate literal contraint specs into functional ones |
Classes
| AltConstraints(*constraints) | Logical OR for constraints. |
| Classifier([space]) | Abstract classifier class to be inherited by all classifiers |
| ConditionalAttribute([enabled]) | Simple container intended to conditionally store the value |
| Constraint | Base class for input value conversion/validation. |
| Constraints(*constraints) | Logical AND for constraints. |
| Dataset(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes. |
| EnsureBool | Ensure that an input is a bool. |
| EnsureChoice(*values) | Ensure an input is element of a set of possible values |
| EnsureDType(dtype) | Ensure that an input (or several inputs) are of a particular data type. |
| EnsureFloat() | Ensure that an input (or several inputs) are of a data type ‘float’. |
| EnsureInt() | Ensure that an input (or several inputs) are of a data type ‘int’. |
| EnsureListOf(dtype) | Ensure that an input is a list of a particular data type |
| EnsureNone | Ensure an input is of value None |
| EnsureRange([min, max]) | Ensure an input is within a particular range |
| EnsureStr | Ensure an input is a string. |
| EnsureTupleOf(dtype) | Ensure that an input is a tuple of a particular data type |
| Parameter(default[, constraints, ro, index, ...]) | This class shall serve as a representation of a parameter. |
| SMLR(**kwargs) | Sparse Multinomial Logistic Regression Classifier. |
| SMLRWeights(clf[, force_train]) | SensitivityAnalyzer that reports the weights SMLR trained |
| Sensitivity(clf[, force_train]) | Sensitivities of features for a given Classifier. |
Exceptions
| AltConstraints(*constraints) | Logical OR for constraints. |
| Classifier([space]) | Abstract classifier class to be inherited by all classifiers |
| ConditionalAttribute([enabled]) | Simple container intended to conditionally store the value |
| Constraint | Base class for input value conversion/validation. |
| Constraints(*constraints) | Logical AND for constraints. |
| Dataset(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes. |
| EnsureBool | Ensure that an input is a bool. |
| EnsureChoice(*values) | Ensure an input is element of a set of possible values |
| EnsureDType(dtype) | Ensure that an input (or several inputs) are of a particular data type. |
| EnsureFloat() | Ensure that an input (or several inputs) are of a data type ‘float’. |
| EnsureInt() | Ensure that an input (or several inputs) are of a data type ‘int’. |
| EnsureListOf(dtype) | Ensure that an input is a list of a particular data type |
| EnsureNone | Ensure an input is of value None |
| EnsureRange([min, max]) | Ensure an input is within a particular range |
| EnsureStr | Ensure an input is a string. |
| EnsureTupleOf(dtype) | Ensure that an input is a tuple of a particular data type |
| Parameter(default[, constraints, ro, index, ...]) | This class shall serve as a representation of a parameter. |
| SMLR(**kwargs) | Sparse Multinomial Logistic Regression Classifier. |
| SMLRWeights(clf[, force_train]) | SensitivityAnalyzer that reports the weights SMLR trained |
| Sensitivity(clf[, force_train]) | Sensitivities of features for a given Classifier. |
