Class KMapEstimationResult (2.0.1)

Version 2.0.1

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KMapEstimationResult(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Result of the reidentifiability analysis. Note that these results are an estimation, not exact values.

Attribute

Name

Description

k_map_estimation_histogram

Sequence[`.dlp.AnalyzeDataSourceRiskDetails.KMapEstimationResult.KMapEstimationHistogramBucket`] The intervals [min_anonymity, max_anonymity] do not overlap. If a value doesn't correspond to any such interval, the associated frequency is zero. For example, the following records: {min_anonymity: 1, max_anonymity: 1, frequency: 17} {min_anonymity: 2, max_anonymity: 3, frequency: 42} {min_anonymity: 5, max_anonymity: 10, frequency: 99} mean that there are no record with an estimated anonymity of 4, 5, or larger than 10.

Inheritance

builtins.object > proto.message.Message > KMapEstimationResult

Classes

KMapEstimationHistogramBucket

KMapEstimationHistogramBucket(
    mapping=None, *, ignore_unknown_fields=False, **kwargs
)

A KMapEstimationHistogramBucket message with the following values: min_anonymity: 3 max_anonymity: 5 frequency: 42 means that there are 42 records whose quasi-identifier values correspond to 3, 4 or 5 people in the overlying population. An important particular case is when min_anonymity = max_anonymity = 1: the frequency field then corresponds to the number of uniquely identifiable records.

KMapEstimationQuasiIdValues

KMapEstimationQuasiIdValues(mapping=None, *, ignore_unknown_fields=False, **kwargs)

A tuple of values for the quasi-identifier columns.