mvpa2.clfs.smlrΒΆ

Sparse Multinomial Logistic Regression classifier.

Inheritance diagram of mvpa2.clfs.smlr

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.
Doi(doi[, key])

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.
Doi(doi[, key])

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.