Table 3.
Precision and recall values for the test dataset. Best results are highlighted in bold
| Irrelevant papers | Relevant papers | |||||
|---|---|---|---|---|---|---|
| Classifier | Precision (%) | Recall (%) | F-score (%) | Precision (%) | Recall (%) | F-score (%) |
| RidgeClassifier | 91.6 | 84.1 | 87.7 | 85.8 | 92.6 | 89.1 |
| SGDClassifier | 91.6 | 84.5 | 87.9 | 86.2 | 92.6 | 89.3 |
| PassiveAggressiveClassifier | 91.7 | 78.6 | 85.2 | 82.1 | 94.3 | 87.8 |
| LogisticRegression | 93.0 | 78.6 | 85.2 | 82.1 | 94.3 | 87.8 |
| MultinomialNB | 95.7 | 60.9 | 74.4 | 72.2 | 97.4 | 82.9 |
| ComplementNB | 92.6 | 68.6 | 78.9 | 75.9 | 94.8 | 84.3 |
| BernoulliNB | 96.2 | 69.5 | 80.7 | 76.9 | 97.4 | 85.9 |
| DecisionTreeClassifier | 93.9 | 91.5 | 92.4 | 90.9 | 94.3 | 92.9 |
| RandomForestClassifier | 95.1 | 79.5 | 86.5 | 83.0 | 96.1 | 89.1 |
| BaggingClassifier | 96.3 | 94.1 | 95.2 | 94.4 | 96.5 | 95.5 |
| KNeighborsClassifier | 89.0 | 70.0 | 78.4 | 76.1 | 91.7 | 83.2 |
| AdaBoostClassifier | 94.1 | 87.3 | 90.6 | 88.6 | 94.8 | 91.6 |
| SVC | 88.8 | 86.8 | 87.8 | 87.6 | 89.5 | 88.6 |
| MLPClassifier | 94.9 | 84.1 | 89.2 | 86.2 | 95.6 | 90.7 |