mvpa.clfs.blr

Bayesian Linear Regression (BLR).

The comprehensive API documentation for this module, including all technical details, is available in the Epydoc-generated API reference for mvpa.clfs.blr (for developers).

BLR

class mvpa.clfs.blr.BLR(sigma_p=None, sigma_noise=1.0, **kwargs)

Bases: mvpa.clfs.base.Classifier

Bayesian Linear Regression (BLR).

Note

Available state variables:

• feature_ids: Feature IDS which were used for the actual training.
• log_marginal_likelihood: Log Marginal Likelihood
• predicted_variances: Variance per each predicted value
• predicting_time+: Time (in seconds) which took classifier to predict
• predictions+: Most recent set of predictions
• trained_dataset: The dataset it has been trained on
• trained_labels+: Set of unique labels it has been trained on
• training_confusion: Confusion matrix of learning performance
• training_time+: Time (in seconds) which took classifier to train
• values+: Internal classifier values the most recent predictions are based on

(States enabled by default are listed with +)

See also

Please refer to the documentation of the base class for more information:

Classifier

Initialize a BLR regression analysis.

Parameters:

• sigma_noise (float) – the standard deviation of the gaussian noise. (Defaults to 0.1)
• regression – Either to use ‘regression’ as regression. By default any Classifier-derived class serves as a classifier, so regression does binary classification. (Default: False)
• enable_states (None or list of basestring) – Names of the state variables which should be enabled additionally to default ones
• disable_states (None or list of basestring) – Names of the state variables which should be disabled

compute_log_marginal_likelihood()

Compute log marginal likelihood using self.train_fv and self.labels.

set_hyperparameters(*args)

Set hyperparameters’ values.

Note that this is a list so the order of the values is important.

See also

Derived classes might provide additional methods via their base classes. Please refer to the list of base classes (if it exists) at the begining of the BLR documentation.

Full API documentation of BLR in module mvpa.clfs.blr.