Inherited from base.Classifier: __str__, clone, getSensitivityAnalyzer, isTrained, predict, repredict, retrain, summary, train, trained, untrain

Inherited from base.Classifier (private): _getFeatureIds, _postpredict, _posttrain, _prepredict, _pretrain, _regressionIsBogus, _setRetrainable

Inherited from misc.state.ClassWithCollections: __getattribute__, __new__, __setattr__, reset

Inherited from object: __delattr__, __format__, __hash__, __reduce__, __reduce_ex__, __sizeof__, __subclasshook__

Class Variables

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_clf_internals = ['plr', 'binary', 'linear']
Describes some specifics about the classifier -- is that it is doing regression for instance....

Inherited from base.Classifier: _DEV__doc__, feature_ids, predicting_time, predictions, regression, retrainable, trained_dataset, trained_labels, trained_nsamples, training_confusion, training_time, values

Inherited from misc.state.ClassWithCollections: descr

Properties

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Inherited from object: __class__

Method Details

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init(self, lm=1, criterion=1, reduced=0.0, maxiter=20, **kwargs)
(Constructor)

source code

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.

Overrides: object.__init__