[BUG] Running ProfitabilityProsecutor with an already suppressed dataset (GUI and API)

[mhalilovic]

I encounter an error when anonymizing a fully suppressed dataset using the API, with similar behavior observed in the GUI.

Example to reproduce using the ARX GUI:
Import a fully suppressed dataset (all * values), applying generalization hierarchies with just one level *
Configured Profitability Prosecutor with suppression limit of 100%.

When attempting to anonymize, I get the message: Cannot anonymize data: Value (NaN) out of range [0,1]

Description of the API behavior:
The same issue appears to occur when using the API with Java.
Here is part of my logs:
Caused by: java.lang.IllegalStateException: Value (NaN) out of range [0,1]
at org.deidentifier.arx.metric.v2.MetricSDNMEntropyBasedInformationLoss.getEntropyBasedInformationLoss(MetricSDNMEntropyBasedInformationLoss.java:109)
at org.deidentifier.arx.criteria.ProfitabilityProsecutor.isAnonymous(ProfitabilityProsecutor.java:121)
at org.deidentifier.arx.framework.check.groupify.HashGroupify.isPrivacyModelFulfilled(HashGroupify.java:758)
at org.deidentifier.arx.framework.check.groupify.HashGroupify.analyzeWithEarlyAbort(HashGroupify.java:653)
at org.deidentifier.arx.framework.check.groupify.HashGroupify.stateAnalyze(HashGroupify.java:447)
at org.deidentifier.arx.framework.check.TransformationChecker.check(TransformationChecker.java:217)
at org.deidentifier.arx.framework.check.TransformationChecker.check(TransformationChecker.java:170)
at org.deidentifier.arx.algorithm.FLASHAlgorithmImpl.traverse(FLASHAlgorithmImpl.java:128)
at org.deidentifier.arx.ARXAnonymizer.anonymize(ARXAnonymizer.java:777)
at org.deidentifier.arx.ARXAnonymizer.anonymize(ARXAnonymizer.java:226)
at org.deidentifier.arx.distributed.ARXWorkerLocal$1.call(Unknown Source)
at org.deidentifier.arx.distributed.ARXWorkerLocal$1.call(Unknown Source)

[prasser]

This should be relatively easy to fix. Can you please investigate the semantics of the number [0, 1] usually returned from getEntropyBasedInformationLoss? Is it 0 for no information loss and 1 for maximum information loss, or the other way around (0 for maximum information loss and 1 for no information loss)? Please let me know here.

[mhalilovic]

0 for no information loss and 1 for maximum information loss

[prasser]

Please check whether the recent commit 984f38f fixes the problem.

[mhalilovic]

My issue with the API is resolved. Thank you!

The GUI also "anonymizes" the dataset now without a message.
Most quality models have NaN or N/A values in the Quality models tab now. I do not know if this is expected behavior.

[prasser]

Most quality models have NaN or N/A values in the Quality models tab now. I do not know if this is expected behavior.

Are you sure that this is caused by this commit? Please check.