SingleTableMetric()
SingleTableMetric
Base class for metrics that apply to single tables.
SingleTableMetric.get_subclasses([…])
SingleTableMetric.get_subclasses
Recursively find subclasses of this metric.
MultiColumnPairsMetric(column_pairs_metric, …)
MultiColumnPairsMetric
SingleTableMetric subclass that applies a ColumnPairsMetric on each possible column pair.
MultiColumnPairsMetric.get_subclasses([…])
MultiColumnPairsMetric.get_subclasses
MultiSingleColumnMetric([single_column_metric])
MultiSingleColumnMetric
SingleTableMetric subclass that applies a SingleColumnMetric on each column.
MultiSingleColumnMetric.get_subclasses([…])
MultiSingleColumnMetric.get_subclasses
BNLikelihood()
BNLikelihood
BayesianNetwork Likelihood Single Table metric.
BNLikelihood.get_subclasses([include_parents])
BNLikelihood.get_subclasses
BNLikelihood.compute(real_data, synthetic_data)
BNLikelihood.compute
Compute this metric.
BNLogLikelihood()
BNLogLikelihood
BayesianNetwork Log Likelihood Single Table metric.
BNLogLikelihood.get_subclasses([include_parents])
BNLogLikelihood.get_subclasses
BNLogLikelihood.compute(real_data, …[, …])
BNLogLikelihood.compute
CSTest([single_column_metric])
CSTest
MultiSingleColumnMetric based on SingleColumn CSTest.
CSTest.get_subclasses([include_parents])
CSTest.get_subclasses
CSTest.compute(real_data, synthetic_data[, …])
CSTest.compute
KSTest([single_column_metric])
KSTest
MultiSingleColumnMetric based on SingleColumn KSTest.
KSTest.get_subclasses([include_parents])
KSTest.get_subclasses
KSTest.compute(real_data, synthetic_data[, …])
KSTest.compute
KSTestExtended([single_column_metric])
KSTestExtended
KSTest variation that transforms everything to numerical before comparing the tables.
KSTestExtended.get_subclasses([include_parents])
KSTestExtended.get_subclasses
KSTestExtended.compute(real_data, synthetic_data)
KSTestExtended.compute
ContinuousKLDivergence(column_pairs_metric, …)
ContinuousKLDivergence
MultiColumnPairsMetric based on ColumnPairs ContinuousKLDivergence.
ContinuousKLDivergence.get_subclasses([…])
ContinuousKLDivergence.get_subclasses
ContinuousKLDivergence.compute(real_data, …)
ContinuousKLDivergence.compute
DiscreteKLDivergence(column_pairs_metric, …)
DiscreteKLDivergence
MultiColumnPairsMetric based on ColumnPairs DiscreteKLDivergence.
DiscreteKLDivergence.get_subclasses([…])
DiscreteKLDivergence.get_subclasses
DiscreteKLDivergence.compute(real_data, …)
DiscreteKLDivergence.compute
GMLogLikelihood()
GMLogLikelihood
GaussianMixture Single Table metric.
GMLogLikelihood.get_subclasses([include_parents])
GMLogLikelihood.get_subclasses
GMLogLikelihood.compute(real_data, …[, …])
GMLogLikelihood.compute
DetectionMetric()
DetectionMetric
Base class for Machine Learning Detection based metrics on single tables.
DetectionMetric.get_subclasses([include_parents])
DetectionMetric.get_subclasses
ScikitLearnClassifierDetectionMetric()
ScikitLearnClassifierDetectionMetric
Base class for Detection metrics build using Scikit Learn Classifiers.
ScikitLearnClassifierDetectionMetric.get_subclasses([…])
ScikitLearnClassifierDetectionMetric.get_subclasses
LogisticDetection()
LogisticDetection
ScikitLearnClassifierDetectionMetric based on a LogisticRegression.
LogisticDetection.get_subclasses([…])
LogisticDetection.get_subclasses
LogisticDetection.compute(real_data, …[, …])
LogisticDetection.compute
SVCDetection()
SVCDetection
ScikitLearnClassifierDetectionMetric based on a SVC.
SVCDetection.get_subclasses([include_parents])
SVCDetection.get_subclasses
SVCDetection.compute(real_data, synthetic_data)
SVCDetection.compute
MLEfficacyMetric()
MLEfficacyMetric
Base class for Machine Learning Efficacy metrics on single tables.
MLEfficacyMetric.get_subclasses([…])
MLEfficacyMetric.get_subclasses
BinaryEfficacyMetric()
BinaryEfficacyMetric
Base class for Binary Classification Efficacy metrics.
BinaryEfficacyMetric.get_subclasses([…])
BinaryEfficacyMetric.get_subclasses
BinaryDecisionTreeClassifier()
BinaryDecisionTreeClassifier
Binary DecisionTreeClassifier Efficacy based metric.
BinaryDecisionTreeClassifier.get_subclasses([…])
BinaryDecisionTreeClassifier.get_subclasses
BinaryDecisionTreeClassifier.compute(…[, …])
BinaryDecisionTreeClassifier.compute
BinaryAdaBoostClassifier()
BinaryAdaBoostClassifier
Binary AdaBoostClassifier Efficacy based metric.
BinaryAdaBoostClassifier.get_subclasses([…])
BinaryAdaBoostClassifier.get_subclasses
BinaryAdaBoostClassifier.compute(real_data, …)
BinaryAdaBoostClassifier.compute
BinaryLogisticRegression()
BinaryLogisticRegression
Binary LogisticRegression Efficacy based metric.
BinaryLogisticRegression.get_subclasses([…])
BinaryLogisticRegression.get_subclasses
BinaryLogisticRegression.compute(real_data, …)
BinaryLogisticRegression.compute
BinaryMLPClassifier()
BinaryMLPClassifier
Binary MLPClassifier Efficacy based metric.
BinaryMLPClassifier.get_subclasses([…])
BinaryMLPClassifier.get_subclasses
BinaryMLPClassifier.compute(real_data, …)
BinaryMLPClassifier.compute
MulticlassEfficacyMetric()
MulticlassEfficacyMetric
Base class for Multiclass Classification Efficacy Metrics.
MulticlassDecisionTreeClassifier()
MulticlassDecisionTreeClassifier
Multiclass DecisionTreeClassifier Efficacy based metric.
MulticlassDecisionTreeClassifier.get_subclasses([…])
MulticlassDecisionTreeClassifier.get_subclasses
MulticlassDecisionTreeClassifier.compute(…)
MulticlassDecisionTreeClassifier.compute
MulticlassMLPClassifier()
MulticlassMLPClassifier
Multiclass MLPClassifier Efficacy based metric.
MulticlassMLPClassifier.get_subclasses([…])
MulticlassMLPClassifier.get_subclasses
MulticlassMLPClassifier.compute(real_data, …)
MulticlassMLPClassifier.compute
RegressionEfficacyMetric()
RegressionEfficacyMetric
RegressionEfficacy base class.
LinearRegression()
LinearRegression
LinearRegression Efficacy based metric.
LinearRegression.get_subclasses([…])
LinearRegression.get_subclasses
LinearRegression.compute(real_data, …[, …])
LinearRegression.compute
MLPRegressor()
MLPRegressor
MLPRegressor Efficacy based metric.
MLPRegressor.get_subclasses([include_parents])
MLPRegressor.get_subclasses
MLPRegressor.compute(real_data, synthetic_data)
MLPRegressor.compute
CategoricalPrivacyMetric()
CategoricalPrivacyMetric
Base class for Categorical Privacy metrics on single tables.
CategoricalPrivacyMetric.get_subclasses([…])
CategoricalPrivacyMetric.get_subclasses
NumericalPrivacyMetric()
NumericalPrivacyMetric
Base class for Numerical Privacy metrics on single tables.
NumericalPrivacyMetric.get_subclasses([…])
NumericalPrivacyMetric.get_subclasses
CategoricalCAP()
CategoricalCAP
The Categorical CAP privacy metric.
CategoricalCAP.get_subclasses([include_parents])
CategoricalCAP.get_subclasses
CategoricalCAP.compute(real_data, synthetic_data)
CategoricalCAP.compute
CategoricalZeroCAP()
CategoricalZeroCAP
The Categorical 0CAP privacy metric.
CategoricalZeroCAP.get_subclasses([…])
CategoricalZeroCAP.get_subclasses
CategoricalZeroCAP.compute(real_data, …[, …])
CategoricalZeroCAP.compute
CategoricalGeneralizedCAP()
CategoricalGeneralizedCAP
The GeneralizedCAP privacy metric.
CategoricalGeneralizedCAP.get_subclasses([…])
CategoricalGeneralizedCAP.get_subclasses
CategoricalGeneralizedCAP.compute(real_data, …)
CategoricalGeneralizedCAP.compute
CategoricalKNN()
CategoricalKNN
The Categorical KNN privacy metric.
CategoricalKNN.get_subclasses([include_parents])
CategoricalKNN.get_subclasses
CategoricalKNN.compute(real_data, synthetic_data)
CategoricalKNN.compute
CategoricalNB()
CategoricalNB
The Categorical NaiveBaysian privacy metric.
CategoricalNB.get_subclasses([include_parents])
CategoricalNB.get_subclasses
CategoricalNB.compute(real_data, synthetic_data)
CategoricalNB.compute
CategoricalRF()
CategoricalRF
The Categorical RF privacy metric.
CategoricalRF.get_subclasses([include_parents])
CategoricalRF.get_subclasses
CategoricalRF.compute(real_data, synthetic_data)
CategoricalRF.compute
CategoricalSVM()
CategoricalSVM
The Categorical SVM privacy metric.
CategoricalSVM.get_subclasses([include_parents])
CategoricalSVM.get_subclasses
CategoricalSVM.compute(real_data, synthetic_data)
CategoricalSVM.compute
NumericalMLP()
NumericalMLP
The Multi-layer Perceptron regression privacy metric.
NumericalMLP.get_subclasses([include_parents])
NumericalMLP.get_subclasses
NumericalMLP.compute(real_data, synthetic_data)
NumericalMLP.compute
NumericalLR()
NumericalLR
The Numerical Linear Regression privacy metric.
NumericalLR.get_subclasses([include_parents])
NumericalLR.get_subclasses
NumericalLR.compute(real_data, synthetic_data)
NumericalLR.compute
NumericalSVR()
NumericalSVR
The Numerical Support-vector Regression privacy metric.
NumericalSVR.get_subclasses([include_parents])
NumericalSVR.get_subclasses
NumericalSVR.compute(real_data, synthetic_data)
NumericalSVR.compute
CategoricalEnsemble()
CategoricalEnsemble
The Categorical Ensemble privacy metric.
CategoricalEnsemble.get_subclasses([…])
CategoricalEnsemble.get_subclasses
CategoricalEnsemble.compute(real_data, …)
CategoricalEnsemble.compute
NumericalRadiusNearestNeighbor()
NumericalRadiusNearestNeighbor
The Radius Nearest Neighbor privacy metric.
NumericalRadiusNearestNeighbor.get_subclasses([…])
NumericalRadiusNearestNeighbor.get_subclasses
NumericalRadiusNearestNeighbor.compute(…)
NumericalRadiusNearestNeighbor.compute