characteristic 发表于 2025-4-1 03:54:59
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Types of Interval Data Sets: Towards Feasible Algorithmsharacteristics are mean and variance. We already know that computing the mean under interval uncertainty is straightforward. However, as the previous chapter shows, computing variance . under interval uncertainty is, in general, an NP-hard (computationally difficult) problem. As we will see in the f馆长 发表于 2025-4-1 11:08:26
Computing Variance under Interval Uncertainty: Efficient Algorithmsnt . can be always computed in feasible (polynomial) time). Since we cannot always efficiently compute the upper endpoint . , we therefore need to consider cases when such an efficient computation may be possible.Fierce 发表于 2025-4-1 17:31:21
Computing Variance under Hierarchical Privacy-Related Interval Uncertaintye desired statistical characteristics..To prevent privacy violations, we replace the original values of the quasiidentifier variables with ranges. For example, we divide the set of all possible ages into ranges , , , etc. Then, instead of storing the actual age of 26, we only