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clfs.plr

Module: clfs.plr

Inheritance diagram for mvpa.clfs.plr:

Penalized logistic regression classifier.

PLR

class mvpa.clfs.plr.PLR(lm=1, criterion=1, reduced=0.0, maxiter=20, **kwargs)

Bases: mvpa.clfs.base.Classifier

Penalized logistic regression Classifier.

Note

Available state variables:

• feature_ids: Feature IDS which were used for the actual training.
• 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
• trained_nsamples+: Number of samples 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 penalized logistic regression analysis

Parameters:

• lm (int) – the penalty term lambda.
• criterion (int) – the criterion applied to judge convergence.
• reduced (float) – if not 0, the rank of the data is reduced before performing the calculations. In that case, reduce is taken as the fraction of the first singular value, at which a dimension is not considered significant anymore. A reasonable criterion is reduced=0.01
• maxiter (int) – maximum number of iterations. If no convergence occurs after this number of iterations, an exception is raised.
• 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