Synthetic equivalence-class size audit
Count identical quasi-identifier patterns and flag small groups in synthetic data.
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Use synthetic categories only, never patient records. First line is integer k≥2; remaining rows must have the same 1–10 fields. Literal comma splitting only; quoted CSV is unsupported.
The starting values are hypothetical. Results update as you edit. Use aggregate or synthetic inputs only.
Calculation results
- Rows
- 4
- Distinct equivalence classes
- 3
- Minimum class size
- 1
- Rows in classes below target k
- 4
- Target k
- 3
- Privacy interpretation
- A class-size audit only; not anonymization or a privacy guarantee.
How to interpret the output
The minimum equivalence-class size measures how many rows share the selected quasi-identifiers. Meeting k alone does not guarantee anonymity, prevent attribute disclosure or satisfy legal privacy requirements. Selection of identifiers, linkage attacks and sensitive-value diversity need a full disclosure-risk assessment.
Method referenceSource checked 2026-11-06. Read the reproducible calculator validation report.