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 | [hide private]

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

Instance Methods | [hide private]

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

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

summary(self) Provide summary for the CombinedClassifier. | source code

untrain(self) Untrain CombinedClassifier | source code

_train(self, dataset) Train CombinedClassifier | source code

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

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 | [hide private]

| 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 | [hide private]

| __combiner Functor destined to combine results of multiple classifiers

Properties | [hide private]

Inherited from `object`: `__class__`

Method Details | [hide private]

### __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)

source code

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

### untrain(self)

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Untrain CombinedClassifier

Overrides: base.Classifier.untrain

### _train(self, dataset)

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Train CombinedClassifier

Overrides: base.Classifier._train

### _predict(self, data)

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Predict using CombinedClassifier

Overrides: base.Classifier._predict

Class Variable Details | [hide private]

### combiner

Value:

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