Package mvpa :: Package clfs :: Module meta :: Class ProxyClassifier

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# Class ProxyClassifier

source code

Classifier which decorates another classifier

Possible uses:

> - modify data somehow prior training/testing: * normalization * feature selection * modification
> - optimized classifier?

Nested Classes | [hide private]

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

Instance Methods | [hide private]

__init__(self, clf, **kwargs) Initialize the instance | source code

__repr__(self, prefixes=[]) String definition of the object of ClassWithCollections object | source code

summary(self) Providing summary over the classifier | source code

_train(self, dataset) Train ProxyClassifier | source code

_predict(self, data) Predict using ProxyClassifier | source code

untrain(self) Untrain ProxyClassifier | source code

getSensitivityAnalyzer(self, slave_kwargs, **kwargs) Return an appropriate SensitivityAnalyzer | source code

Inherited from `base.Classifier`: `__str__`, `clone`, `isTrained`, `predict`, `repredict`, `retrain`, `train`, `trained`

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 = `property(lambda x: x.__clf, doc= "Used `Classifier`")`
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 `base.Classifier` (private): `_clf_internals` Inherited from `misc.state.ClassWithCollections`: `descr`

Instance Variables | [hide private]

| __clf Store the classifier to use.

Properties | [hide private]

Inherited from `object`: `__class__`

Method Details | [hide private]

### __init__(self, clf, **kwargs)
(Constructor)

source code

Initialize the instance

Parameters:
  - `clf` (Classifier) - classifier based on which mask classifiers is created
Overrides: object.__init__

### __repr__(self, prefixes=[])
(Representation operator)

source code

String definition of the object of ClassWithCollections object

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

### summary(self)

source code

Providing summary over the classifier

Overrides: base.Classifier.summary
  (inherited documentation)

### _train(self, dataset)

source code

Train ProxyClassifier

Overrides: base.Classifier._train

### _predict(self, data)

source code

Predict using ProxyClassifier

Overrides: base.Classifier._predict

### untrain(self)

source code

Untrain ProxyClassifier

Overrides: base.Classifier.untrain

### getSensitivityAnalyzer(self, slave_kwargs, **kwargs)

source code

Return an appropriate SensitivityAnalyzer

Decorators:
  - `@group_kwargs(prefixes= ['slave_'], passthrough= True)`
Overrides: base.Classifier.getSensitivityAnalyzer