Sparse Multinomial Logistic Regression classifier.
Functions
Doi(*args, **kwargs) | Perform no good and no bad |
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. |