Research Article
QuPiD Attack: Machine Learning-Based Privacy Quantification Mechanism for PIR Protocols in Health-Related Web Search
Table 8
Precision and recall of clean dataset in different groups.
| Group | Group 1 | Group 2 | Group 3 | Group 4 | Group 5 |
| Tree-based | J48 | Precision | 0.66 | 0.62 | 0.73 | 0.80 | 0.76 | Recall | 0.62 | 0.60 | 0.71 | 0.81 | 0.78 | LMT | Precision | 0.62 | 0.66 | 0.73 | 0.75 | 0.75 | Recall | 0.66 | 0.61 | 0.65 | 0.79 | 0.75 |
| Rule-based | Decision Table | Precision | 0.84 | 0.81 | 0.79 | 0.92 | 0.81 | Recall | 0.58 | 0.51 | 0.63 | 0.79 | 0.74 | JRip | Precision | 0.73 | 0.82 | 0.83 | 0.88 | 0.75 | Recall | 0.40 | 0.35 | 0.42 | 0.63 | 0.59 | OneR | Precision | 0.41 | 0.37 | 0.43 | 0.55 | 0.48 | Recall | 0.38 | 0.28 | 0.41 | 0.60 | 0.55 |
| Lazy learner | IBK | Precision | 0.72 | 0.70 | 0.80 | 0.85 | 0.80 | Recall | 0.71 | 0.69 | 0.76 | 0.85 | 0.83 | KStar | Precision | 0.74 | 0.75 | 0.73 | 0.77 | 0.77 | Recall | 0.69 | 0.62 | 0.71 | 0.80 | 0.78 |
| Metaheuristic | Bagging | Precision | 0.75 | 0.71 | 0.75 | 0.81 | 0.75 | Recall | 0.65 | 0.61 | 0.71 | 0.82 | 0.81 | LogitBoost | Precision | 0.42 | 0.17 | 0.29 | 0.39 | 0.20 | Recall | 0.19 | 0.14 | 0.23 | 0.34 | 0.38 |
| Bayesian | Bayes Net | Precision | 0.79 | 0.74 | 0.71 | 0.77 | 0.57 | Recall | 0.45 | 0.45 | 0.59 | 0.74 | 0.73 |
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