tapas.attacks.set_classifiers

Classes

CombinedSetFeatures(*features)	Combined (concatenated) set features extracted from datasets.
CorrSetFeature()	F_Corr set feature from Stadler et al. Compute linear correlation between features.
FeatureBasedSetClassifier(features, classifier)	Classifier that first computes a representation of the dataset and then uses 'traditional' (vector-based) classification techniques.
HistSetFeature([num_bins, bounds])	F_Hist set feature from Stadler et al. Compute a histogram of each column, with binning for continuous variables.
NaiveSetFeature()	Naive set feature F_Naive from Stadler et al. Mean, median, and variance of each column is computed.
RandomTargetedQueryFeature(target, order, number)	Features that computes random targeted queries that include the user.
SetClassifier()	Abstract base class for classifiers over set-valued data.
SetFeature()	Represents a set of features that can be extracted from a dataset, as a np.array vector.