Package mvpa :: Package clfs :: Module meta :: Class BoostedClassifier

[hide private]
[frames] | no frames]

# Class BoostedClassifier

source code

Classifier containing the farm of other classifiers.

Should rarely be used directly. Use one of its childs instead

Nested Classes | [hide private]

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

Instance Methods | [hide private]

__init__(self, clfs=None, propagate_states=True, harvest_attribs=None, copy_attribs='copy', **kwargs) Initialize the instance. | source code

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

_train(self, dataset) Train BoostedClassifier | source code

_posttrain(self, dataset) Custom posttrain of BoostedClassifier | source code

_getFeatureIds(self) Custom _getFeatureIds for BoostedClassifier | source code

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

_setClassifiers(self, clfs) Set the classifiers used by the boosted classifier | source code

untrain(self) Untrain BoostedClassifier | source code

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

Inherited from `base.Classifier`: `__str__`, `clone`, `isTrained`, `predict`, `repredict`, `retrain`, `summary`, `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]

| raw_predictions = `StateVariable(enabled= False, doc= "Predicti`...``
| raw_values = `StateVariable(enabled= False, doc= "Values obtain`...``
| clfs = `property(fget= lambda x: x.__clfs, fset= _setClassifier`...``

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]

| __propagate_states Enable current enabled states in slave classifiers
| __clfs Classifiers to use

Properties | [hide private]

Inherited from `object`: `__class__`

Method Details | [hide private]

### __init__(self, clfs=None, propagate_states=True, harvest_attribs=None, copy_attribs='copy', **kwargs)
(Constructor)

source code

Initialize the instance.

Parameters:
  - `clfs` (list) - list of classifier instances to use (slave classifiers)
  - `propagate_states` (bool) - either to propagate enabled states into slave classifiers. It is in effect only when slaves get assigned - so if state is enabled not during construction, it would not necessarily propagate into slaves
  - `kwargs` (dict) - dict of keyworded arguments which might get used by State or Classifier
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)

### _train(self, dataset)

source code

Train BoostedClassifier

Overrides: base.Classifier._train

### _posttrain(self, dataset)

source code

Custom posttrain of BoostedClassifier

Harvest over the trained classifiers if it was asked to so

Overrides: base.Classifier._posttrain

### _getFeatureIds(self)

source code

Custom _getFeatureIds for BoostedClassifier

Overrides: base.Classifier._getFeatureIds

### _predict(self, data)

source code

Predict using BoostedClassifier

Overrides: base.Classifier._predict

### _setClassifiers(self, clfs)

source code

Set the classifiers used by the boosted classifier

We have to allow to set list of classifiers after the object was actually created. It will be used by MulticlassClassifier

### untrain(self)

source code

Untrain BoostedClassifier

Has to untrain any known classifier

Overrides: base.Classifier.untrain

### getSensitivityAnalyzer(self, **kwargs)

source code

Return an appropriate SensitivityAnalyzer

Overrides: base.Classifier.getSensitivityAnalyzer

Class Variable Details | [hide private]

### raw_predictions

Value:

      StateVariable(enabled= False, doc= "Predictions obtained from each cla
      ssifier")

### raw_values

Value:

      StateVariable(enabled= False, doc= "Values obtained from each classifi
      er")

### clfs

Value:

      property(fget= lambda x: x.__clfs, fset= _setClassifiers, doc= "Used c
      lassifiers")