/** * Returns the test cases. * * @return */ @Parameters(name = "{index}:[{0}]") public static Collection<Object[]> cases() { return Arrays.asList( new Object[][] { /* 0 */ { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createPrecomputedEntropyMetric(0.1d, true)) .addPrivacyModel(new KAnonymity(5)), "./data/adult.csv", 255559.85455731067, new int[] {1, 0, 1, 1, 3, 2, 2, 0, 1}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createPrecomputedEntropyMetric(0.1d, true)) .addPrivacyModel(new KAnonymity(100)), "./data/adult.csv", 379417.3460570988, new int[] {1, 1, 1, 1, 3, 2, 2, 1, 1}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.0d, Metric.createPrecomputedEntropyMetric(0.1d, true)) .addPrivacyModel(new KAnonymity(5)), "./data/adult.csv", 407289.5388925293, new int[] {1, 2, 1, 1, 3, 2, 2, 1, 1}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.0d, Metric.createPrecomputedEntropyMetric(0.1d, true)) .addPrivacyModel(new KAnonymity(100)), "./data/adult.csv", 453196.8932458743, new int[] {0, 4, 1, 1, 3, 2, 2, 1, 1}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createPrecomputedEntropyMetric(0.1d, true)) .addPrivacyModel(new KAnonymity(5)), "./data/adult.csv", 255559.85455731067, new int[] {1, 0, 1, 1, 3, 2, 2, 0, 1}, true) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createPrecomputedEntropyMetric(0.1d, true)) .addPrivacyModel(new KAnonymity(100)), "./data/adult.csv", 379417.3460570988, new int[] {1, 1, 1, 1, 3, 2, 2, 1, 1}, true) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createPrecomputedEntropyMetric(0.1d, false)) .addPrivacyModel(new KAnonymity(5)), "./data/cup.csv", 1764006.4033760305, new int[] {2, 4, 0, 1, 0, 4, 4, 4}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createPrecomputedEntropyMetric(0.1d, false)) .addPrivacyModel(new KAnonymity(100)), "./data/cup.csv", 1994002.8308631124, new int[] {3, 4, 1, 1, 0, 4, 4, 4}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.0d, Metric.createPrecomputedEntropyMetric(0.1d, false)) .addPrivacyModel(new KAnonymity(5)), "./data/cup.csv", 2445878.424834677, new int[] {4, 4, 1, 1, 1, 4, 4, 4}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.0d, Metric.createPrecomputedEntropyMetric(0.1d, false)) .addPrivacyModel(new KAnonymity(100)), "./data/cup.csv", 2517471.5816586106, new int[] {5, 4, 1, 0, 1, 4, 4, 4}, false) }, /* 10 */ { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createPrecomputedEntropyMetric(0.1d, false)) .addPrivacyModel(new KAnonymity(5)), "./data/cup.csv", 1764006.4033760305, new int[] {2, 4, 0, 1, 0, 4, 4, 4}, true) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createPrecomputedEntropyMetric(0.1d, false)) .addPrivacyModel(new KAnonymity(100)), "./data/cup.csv", 2001343.4737485605, new int[] {3, 4, 1, 1, 0, 1, 2, 1}, true) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createDiscernabilityMetric(true)) .addPrivacyModel(new KAnonymity(5)), "./data/fars.csv", 4469271.0, new int[] {0, 2, 2, 2, 1, 2, 1, 0}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createDiscernabilityMetric(true)) .addPrivacyModel(new KAnonymity(100)), "./data/fars.csv", 5.6052481E7, new int[] {0, 2, 3, 3, 1, 2, 2, 2}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.0d, Metric.createDiscernabilityMetric(true)) .addPrivacyModel(new KAnonymity(5)), "./data/fars.csv", 1.42377891E8, new int[] {1, 2, 3, 3, 1, 2, 1, 2}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.0d, Metric.createDiscernabilityMetric(true)) .addPrivacyModel(new KAnonymity(100)), "./data/fars.csv", 4.36925397E8, new int[] {5, 2, 3, 3, 1, 2, 0, 2}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createDiscernabilityMetric(true)) .addPrivacyModel(new KAnonymity(5)), "./data/fars.csv", 4469271.0, new int[] {0, 2, 2, 2, 1, 2, 1, 0}, true) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createDiscernabilityMetric(true)) .addPrivacyModel(new KAnonymity(100)), "./data/fars.csv", 5.6052481E7, new int[] {0, 2, 3, 3, 1, 2, 2, 2}, true) }, }); }
/** * Returns the test cases. * * @return */ @Parameters(name = "{index}:[{0}]") public static Collection<Object[]> cases() { return Arrays.asList( new Object[][] { /* 0 */ { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createPrecomputedEntropyMetric(0.1d, false)) .addPrivacyModel( new EntropyLDiversity("occupation", 5, EntropyEstimator.GRASSBERGER)), "occupation", "./data/adult.csv", 216092.124036387, new int[] {1, 0, 1, 0, 3, 2, 2, 0}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createPrecomputedEntropyMetric(0.1d, false)) .addPrivacyModel( new EntropyLDiversity("occupation", 100, EntropyEstimator.SHANNON)), "occupation", "./data/adult.csv", 0.0d, null, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.0d, Metric.createPrecomputedEntropyMetric(0.1d, false)) .addPrivacyModel( new EntropyLDiversity("occupation", 5, EntropyEstimator.GRASSBERGER)), "occupation", "./data/adult.csv", 324620.5269918692, new int[] {1, 1, 1, 1, 3, 2, 2, 1}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.05d, Metric.createPrecomputedEntropyMetric(0.1d, false)) .addPrivacyModel( new EntropyLDiversity("occupation", 3, EntropyEstimator.GRASSBERGER)), "occupation", "./data/adult.csv", 180347.4325366015, new int[] {0, 0, 1, 1, 2, 2, 2, 0}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createPrecomputedEntropyMetric(0.1d, false)) .addPrivacyModel( new EntropyLDiversity("occupation", 5, EntropyEstimator.SHANNON)), "occupation", "./data/adult.csv", 228878.2039109517, new int[] {1, 0, 1, 1, 2, 2, 2, 1}, true) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.1d, Metric.createPrecomputedEntropyMetric(0.1d, false)) .addPrivacyModel( new EntropyLDiversity("occupation", 100, EntropyEstimator.GRASSBERGER)), "occupation", "./data/adult.csv", 0.0d, null, true) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createDiscernabilityMetric(true)) .addPrivacyModel( new EntropyLDiversity("RAMNTALL", 5, EntropyEstimator.GRASSBERGER)), "RAMNTALL", "./data/cup.csv", 1833435.0, new int[] {4, 0, 1, 0, 1, 3, 1}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.03d, Metric.createDiscernabilityMetric(true)) .addPrivacyModel( new EntropyLDiversity("RAMNTALL", 100, EntropyEstimator.GRASSBERGER)), "RAMNTALL", "./data/cup.csv", 4.5168281E7, new int[] {4, 4, 0, 0, 1, 3, 1}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.0d, Metric.createDiscernabilityMetric(true)) .addPrivacyModel(new EntropyLDiversity("RAMNTALL", 5)), "RAMNTALL", "./data/cup.csv", 3.01506905E8, new int[] {4, 4, 1, 1, 1, 4, 4}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.0d, Metric.createDiscernabilityMetric(true)) .addPrivacyModel(new EntropyLDiversity("RAMNTALL", 3)), "RAMNTALL", "./data/cup.csv", 9.2264547E7, new int[] {4, 4, 1, 0, 1, 4, 4}, false) }, /* 10 */ { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createDiscernabilityMetric(true)) .addPrivacyModel( new EntropyLDiversity("RAMNTALL", 5, EntropyEstimator.SHANNON)), "RAMNTALL", "./data/cup.csv", 2823649.0, new int[] {4, 0, 0, 1, 1, 3, 1}, true) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.1d, Metric.createDiscernabilityMetric(true)) .addPrivacyModel( new EntropyLDiversity("RAMNTALL", 100, EntropyEstimator.GRASSBERGER)), "RAMNTALL", "./data/cup.csv", 3.4459973E7, new int[] {5, 0, 0, 2, 1, 2, 1}, true) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createPrecomputedEntropyMetric(0.1d, true)) .addPrivacyModel( new EntropyLDiversity("EDUC", 5, EntropyEstimator.GRASSBERGER)), "EDUC", "./data/ihis.csv", 7735322.29514608, new int[] {0, 0, 0, 1, 3, 0, 0, 1}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createPrecomputedEntropyMetric(0.1d, true)) .addPrivacyModel( new EntropyLDiversity("EDUC", 2, EntropyEstimator.GRASSBERGER)), "EDUC", "./data/ihis.csv", 5428093.534997522, new int[] {0, 0, 0, 0, 2, 0, 0, 1}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.0d, Metric.createPrecomputedEntropyMetric(0.1d, true)) .addPrivacyModel(new EntropyLDiversity("EDUC", 5, EntropyEstimator.SHANNON)), "EDUC", "./data/ihis.csv", 1.2258628558792587E7, new int[] {0, 0, 0, 3, 3, 2, 0, 1}, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.0d, Metric.createPrecomputedEntropyMetric(0.1d, true)) .addPrivacyModel( new EntropyLDiversity("EDUC", 100, EntropyEstimator.GRASSBERGER)), "EDUC", "./data/ihis.csv", 0.0d, null, false) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.04d, Metric.createPrecomputedEntropyMetric(0.1d, true)) .addPrivacyModel( new EntropyLDiversity("EDUC", 5, EntropyEstimator.GRASSBERGER)), "EDUC", "./data/ihis.csv", 7735322.29514608, new int[] {0, 0, 0, 1, 3, 0, 0, 1}, true) }, { new ARXAnonymizationTestCase( ARXConfiguration.create(0.02d, Metric.createPrecomputedEntropyMetric(0.1d, true)) .addPrivacyModel(new EntropyLDiversity("EDUC", 3, EntropyEstimator.SHANNON)), "EDUC", "./data/ihis.csv", 7578152.206004559, new int[] {0, 0, 0, 2, 2, 0, 0, 1}, true) }, }); }