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Package mvpa :: Package clfs :: Module meta :: Class CombinedClassifier

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Class CombinedClassifier

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BoostedClassifier which combines predictions using some PredictionsCombiner functor.

Nested Classes

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Inherited from misc.state.ClassWithCollections: __metaclass__

Instance Methods

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__init__(self, clfs=None, combiner=None, **kwargs)
Initialize the instance.

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__repr__(self, prefixes=[])
Literal representation of CombinedClassifier.

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summary(self)
Provide summary for the CombinedClassifier.

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untrain(self)
Untrain CombinedClassifier

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_train(self, dataset)
Train CombinedClassifier

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_predict(self, data)
Predict using CombinedClassifier

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Inherited from BoostedClassifier: getSensitivityAnalyzer

Inherited from BoostedClassifier (private): _getFeatureIds, _posttrain, _setClassifiers

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

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

Inherited from misc.state.Harvestable (private): _harvest, _setAttribs

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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combiner = property(fget= lambda x: x.__combiner, doc= "Used c...

Inherited from BoostedClassifier: clfs, raw_predictions, raw_values

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.Harvestable: harvest_attribs, harvested

Inherited from misc.state.Harvestable (private): _KNOWN_COPY_METHODS

Inherited from misc.state.ClassWithCollections: descr

Instance Variables

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__combiner
Functor destined to combine results of multiple classifiers

Properties

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Inherited from object: __class__

Method Details

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init(self, clfs=None, combiner=None, **kwargs)
(Constructor)

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Initialize the instance.

NB: combiner might need to operate not on 'predictions' descrete: labels but rather on raw 'class' values classifiers estimate (which is pretty much what is stored under values

Parameters:

clfs (list of Classifier) - list of classifier instances to use
combiner (PredictionsCombiner) - callable which takes care about combining multiple results into a single one (e.g. maximal vote for classification, MeanPrediction for regression))
kwargs (dict) - dict of keyworded arguments which might get used by State or Classifier

Overrides: object.__init__

repr(self, prefixes=[])
(Representation operator)

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Literal representation of CombinedClassifier.

Parameters:

fullname - Either to include full name of the module
prefixes - What other prefixes to prepend to list of arguments

Overrides: object.__repr__

summary(self)

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Provide summary for the CombinedClassifier.

Overrides: base.Classifier.summary

Predict using CombinedClassifier

Overrides: base.Classifier._predict

Class Variable Details

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combiner

Value:

property(fget= lambda x: x.__combiner, doc= "Used combiner to derive a
 single result")

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Class CombinedClassifier

__init__(self, clfs=None, combiner=None, **kwargs) (Constructor)

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

summary(self)

untrain(self)

_train(self, dataset)

_predict(self, data)

combiner

init(self, clfs=None, combiner=None, **kwargs)
(Constructor)

repr(self, prefixes=[])
(Representation operator)