Package org.deidentifier.arx.aggregates
Klasse StatisticsQuality
java.lang.Object
org.deidentifier.arx.aggregates.StatisticsQuality
Encapsulates statistics obtained using various quality models
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Methodenübersicht
Modifizierer und TypMethodeBeschreibungQuality according to the "Ambiguity" model proposed in:
Goldberger, Tassa: "Efficient Anonymizations with Enhanced Utility" Trans Data PrivAttribute-level squared errorReturns a list of all attributes consideredQuality according to the "AECS" model proposed in:
K.DataType<?> getDataType(String attribute) Returns the data type for the attributeQuality according to the "Discernibility" model proposed in:
R.Quality according to the "Precision" model proposed in:
L.Quality according to the "Loss" model proposed in:
Iyengar, V.: "Transforming data to satisfy privacy constraints" Proc Int Conf Knowl Disc Data Mining, p. 279-288 (2002)Returns the fraction of missing values of the attributes consideredQuality according to the "Non-Uniform Entropy" model proposed in:
A.Quality according to the model proposed in:
D.Quality according to the model proposed in:
Solanas, Agusti, Antoni Martinez-Balleste, and J.
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Methodendetails
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getAmbiguity
Quality according to the "Ambiguity" model proposed in:
Goldberger, Tassa: "Efficient Anonymizations with Enhanced Utility" Trans Data Priv- Gibt zurück:
- Quality measure
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getAttributeLevelSquaredError
Attribute-level squared error- Gibt zurück:
- Quality measure
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getAttributes
Returns a list of all attributes considered- Gibt zurück:
- the attributes
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getAverageClassSize
Quality according to the "AECS" model proposed in:
K. LeFevre, D. DeWitt, R. Ramakrishnan: "Mondrian multidimensional k-anonymity" Proc Int Conf Data Engineering, 2006.- Gibt zurück:
- Quality measure
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getDataType
Returns the data type for the attribute- Parameter:
attribute-- Gibt zurück:
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getDiscernibility
Quality according to the "Discernibility" model proposed in:
R. Bayardo, R. Agrawal: "Data privacy through optimal k-anonymization" Proc Int Conf Data Engineering, 2005, pp. 217-228- Gibt zurück:
- Quality measure
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getGeneralizationIntensity
Quality according to the "Precision" model proposed in:
L. Sweeney: "Achieving k-anonymity privacy protection using generalization and suppression" J Uncertain Fuzz Knowl Sys 10 (5) (2002) 571-588.- Gibt zurück:
- Quality measure
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getGranularity
Quality according to the "Loss" model proposed in:
Iyengar, V.: "Transforming data to satisfy privacy constraints" Proc Int Conf Knowl Disc Data Mining, p. 279-288 (2002)- Gibt zurück:
- Quality measure
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getMissings
Returns the fraction of missing values of the attributes considered- Gibt zurück:
- the datatypes
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getNonUniformEntropy
Quality according to the "Non-Uniform Entropy" model proposed in:
A. De Waal and L. Willenborg: "Information loss through global recoding and local suppression" Netherlands Off Stat, vol. 14, pp. 17-20, 1999.- Gibt zurück:
- Quality measure
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getRecordLevelSquaredError
Quality according to the model proposed in:
D. Sanchez, S. Martinez, and J. Domingo-Ferrer. Comment on unique in the shopping mall: On the reidentifiability of credit card metadata. Science, 351(6279):1274-1274, 2016.- Gibt zurück:
- Quality measure
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getSSESST
Quality according to the model proposed in:
Solanas, Agusti, Antoni Martinez-Balleste, and J. Domingo-Ferrer. V-MDAV: a multivariate microaggregation with variable group size. 17th COMPSTAT Symposium of the IASC, Rome. 2006.- Gibt zurück:
- Quality measure
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