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.

Classes

Classifier(**kwargs[, space]) Abstract classifier class to be inherited by all classifiers ..
ConditionalAttribute(*args, **kwargs[, enabled]) Simple container intended to conditionally store the value
Dataset(samples[, sa, fa, a]) Generic storage class for datasets with multiple attributes.
Parameter(default, **kwargs[, ro, index, ...]) This class shall serve as a representation of a parameter.
SMLR(**kwargs) Sparse Multinomial Logistic Regression Classifier.
SMLRWeights(clf, **kwargs[, force_train]) SensitivityAnalyzer that reports the weights SMLR trained
Sensitivity(clf, **kwargs[, force_train]) Sensitivities of features for a given Classifier.

Exceptions

Classifier(**kwargs[, space]) Abstract classifier class to be inherited by all classifiers ..
ConditionalAttribute(*args, **kwargs[, enabled]) Simple container intended to conditionally store the value
Dataset(samples[, sa, fa, a]) Generic storage class for datasets with multiple attributes.
Parameter(default, **kwargs[, ro, index, ...]) This class shall serve as a representation of a parameter.
SMLR(**kwargs) Sparse Multinomial Logistic Regression Classifier.
SMLRWeights(clf, **kwargs[, force_train]) SensitivityAnalyzer that reports the weights SMLR trained
Sensitivity(clf, **kwargs[, force_train]) Sensitivities of features for a given Classifier.

NeuroDebian

NITRC-listed