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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).

Initialize a BLR regression analysis.

Parameters:
  • sigma_noise (float) – the standard deviation of the gaussian noise. (Defaults to 0.1)
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.