Package mvpa :: Package clfs :: Module plr :: Class PLR

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# Class PLR

source code

Penalized logistic regression Classifier.

Nested Classes | [hide private]

Inherited from `misc.state.ClassWithCollections`: `__metaclass__`

Instance Methods | [hide private]

__init__(self, lm=1, criterion=1, reduced=0.0, maxiter=20, **kwargs) Initialize a penalized logistic regression analysis | source code

__repr__(self) String summary over the object | source code

_train(self, data) Train the classifier using `data` (Dataset). | source code

__f(self, y) This is the logistic function f, that is used for determination of the vector w | source code

_predict(self, data) Predict the class labels for the provided data | source code

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 | [hide private]

| _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 | [hide private]

Inherited from `object`: `__class__`

Method Details | [hide private]

### __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__

### __repr__(self)
(Representation operator)

source code

String summary over the object

Parameters:
  - `fullname` - Either to include full name of the module
  - `prefixes` - What other prefixes to prepend to list of arguments
Overrides: object.__repr__

### _train(self, data)

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Train the classifier using `data` (Dataset).

Overrides: base.Classifier._train

### _predict(self, data)

source code

Predict the class labels for the provided data

Returns a list of class labels

Overrides: base.Classifier._predict