Package mvpa :: Package clfs :: Module meta :: Class SplitClassifier
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Class SplitClassifier

source code


BoostedClassifier to work on splits of the data
Nested Classes [hide private]

Inherited from misc.state.ClassWithCollections: __metaclass__

Instance Methods [hide private]
 
__init__(self, clf, splitter=NFoldSplitter(cvtype=1), **kwargs)
Initialize the instance
source code
 
_train(self, dataset)
Train SplitClassifier
source code
 
getSensitivityAnalyzer(self, slave_kwargs, **kwargs)
Return an appropriate SensitivityAnalyzer for SplitClassifier
source code

Inherited from CombinedClassifier: __repr__, summary, untrain

Inherited from CombinedClassifier (private): _predict

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]
  confusion = StateVariable(enabled= False, doc= "Resultant conf...
  splits = StateVariable(enabled= False, doc= """Store the actua...
  splitter = property(fget= lambda x: x.__splitter, doc= "Splitt...

Inherited from CombinedClassifier: combiner

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]
  __clf
Store sample instance of basic classifier
Properties [hide private]

Inherited from object: __class__

Method Details [hide private]

__init__(self, clf, splitter=NFoldSplitter(cvtype=1), **kwargs)
(Constructor)

source code 
Initialize the instance
Parameters:
  • clf (Classifier) - classifier based on which multiple classifiers are created for multiclass
  • splitter (Splitter) - Splitter to use to split the dataset prior training
Overrides: object.__init__

_train(self, dataset)

source code 
Train SplitClassifier
Overrides: base.Classifier._train

getSensitivityAnalyzer(self, slave_kwargs, **kwargs)

source code 
Return an appropriate SensitivityAnalyzer for SplitClassifier
Parameters:
  • combiner - If not provided, FirstAxisMean is assumed
Decorators:
  • @group_kwargs(prefixes= ['slave_'], passthrough= True)
Overrides: base.Classifier.getSensitivityAnalyzer

Class Variable Details [hide private]

confusion

Value:
StateVariable(enabled= False, doc= "Resultant confusion whenever class\
ifier trained "+ "on 1 part and tested on 2nd part of each split")

splits

Value:
StateVariable(enabled= False, doc= """Store the actual splits of the d\
ata. Can be memory expensive""")

splitter

Value:
property(fget= lambda x: x.__splitter, doc= "Splitter user by SplitCla\
ssifier")