/**
* 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)
},
});
}