Table 5 Comparison results of various evaluation metrics from multinomial Naïve Bayes with english Language stopwords removal.
From: Key insights into recommended SMS spam detection datasets
Multinomial Naïve Bayes | |||||||
|---|---|---|---|---|---|---|---|
Dataset | Accuracy | Precision (Ham) | Precision (Spam) | Recall (Ham) | Recall (Spam) | F1 - Score (Ham) | F1 - Score (Spam) |
1 | 98.48% | 0.99 | 0.95 | 0.99 | 0.95 | 0.99 | 0.95 |
2 | 99.03% | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 |
3 | 98.29% | 0.99 | 0.92 | 0.99 | 0.96 | 0.99 | 0.94 |
4 | 89.11% | 0.88 | 0.90 | 0.93 | 0.84 | 0.91 | 0.87 |
5 | 86.10% | 0.93 | 0.77 | 0.85 | 0.89 | 0.88 | 0.83 |
6 | 96.00% | 0.96 | 0.96 | 0.96 | 0.96 | 0.96 | 0.96 |
7 | 93.76% | 0.94 | 0.93 | 0.93 | 0.94 | 0.94 | 0.94 |
8 | 95.20% | 0.94 | 0.96 | 0.95 | 0.95 | 0.95 | 0.96 |
9 | 90.48% | 0.80 | 1.00 | 1.00 | 0.85 | 0.89 | 0.92 |
10 | 83.78% | 0.72 | 0.95 | 0.93 | 0.78 | 0.81 | 0.86 |
