From: Efficient and effective pruning strategies for health data de-identification
Attributes | Transformations | Checked | Inserts | Hits | Antichain |
---|---|---|---|---|---|
3 | 96 | 12 (12.50 %) | 4 | 17.39 % | 75.00 % |
4 | 480 | 50 (10.42 %) | 18 | 20.87 % | 55.56 % |
5 | 1,440 | 89 (6.18 %) | 34 | 22.84 % | 44.12 % |
6 | 4,320 | 177 (4.10 %) | 61 | 25.13 % | 36.07 % |
7 | 12,960 | 449 (3.46 %) | 157 | 28.06 % | 31.85 % |
8 | 38,880 | 820 (2.11 %) | 284 | 29.99 % | 24.65 % |
9 | 116,640 | 3,872 (3.32 %) | 1,187 | 34.26 % | 22.16 % |
10 | 466,560 | 15,858 (3.40 %) | 4,486 | 36.80 % | 22.78 % |
11 | 1,399,680 | 32,507 (2.32 %) | 10,119 | 37.70 % | 20.43 % |
12 | 4,199,040 | 76,679 (1.83 %) | 25,211 | 38.36 % | 18.84 % |
13 | 12,597,120 | 265,762 (2.11 %) | 85,303 | 38.74 % | 19.59 % |
14 | 37,791,360 | 626,383 (1.66 %) | 199,747 | 39.15 % | 20.75 % |
15 | 113,374,080 | 1,634,751 (1.44 %) | 514,863 | 39.31 % | 20.17 % |