Table 5 Space budget in Kbits adopted on the various datasets. \(\epsilon \) is the false positive rate, n is the number of keys in the dataset
From: The role of classifiers and data complexity in learned Bloom filters: insights and recommendations
Data | \({\epsilon }\) | Budget (Kbits) | \({{n}}\) |
|---|---|---|---|
Synthetic | 0.05, 0.01 | 622, 956 | \(10^5\) |
URL | 0.01, 0.005, 0.001, 0.0005, 0.0001 | 765, 880, 1148, 1263, 1530 | \(8\cdot 10^4\) |
DNA | 0.01, 0.005, 0.001, 0.0005, 0.0001 | 477460, 549325, 716191, 788056, 954921 | \(4.99 \cdot 10^7\) |