mvpa2.clfs.meta

Meta classifiers – classifiers which use other classifiers or preprocessing

Meta Classifiers can be grouped according to their function as

group BoostedClassifiers:  CombinedClassifier MulticlassClassifier SplitClassifier group ProxyClassifiers:  ProxyClassifier BinaryClassifier MappedClassifier FeatureSelectionClassifier group PredictionsCombiners for CombinedClassifier:  PredictionsCombiner MaximalVote MeanPrediction

Functions

Classes

BinaryClassifier(clf, poslabels, neglabels, ...)	ProxyClassifier which maps set of two labels into +1 and -1
BoostedClassifier([clfs, propagate_ca])	Classifier containing the farm of other classifiers.
ClassifierCombiner(clf[, variables])	Provides a decision using training a classifier on predictions/estimates
CombinedClassifier([clfs, combiner])	BoostedClassifier which combines predictions using some
FeatureSelectionClassifier(clf, mapper, **kwargs)	This is nothing but a MappedClassifier.
MappedClassifier(clf, mapper, **kwargs)	ProxyClassifier which uses some mapper prior training/testing.
MaximalVote(**kwargs)	Provides a decision using maximal vote rule
MeanPrediction([descr])	Provides a decision by taking mean of the results
MulticlassClassifier(clf[, bclf_type])	Perform multiclass classification using a list of binary classifiers.
PredictionsCombiner([descr])	Base class for combining decisions of multiple classifiers
ProxyClassifier(clf, **kwargs)	Classifier which decorates another classifier
RegressionAsClassifier(clf[, centroids, ...])	Allows to use arbitrary regression for classification.
SplitClassifier(clf[, partitioner, splitter])	BoostedClassifier to work on splits of the data
TreeClassifier(clf, groups, **kwargs)	TreeClassifier which allows to create hierarchy of classifiers