Table 6 The evolution of the error rate of the bayesian network related to the records count in the database
From: A novel lightweight URL phishing detection system using SVM and similarity index
Records count | 100 | 250 | 500 | 750 | 1000 | 1250 | 1500 | 1750 | 2000 |
|---|---|---|---|---|---|---|---|---|---|
Bayes (%) | 52 | 47.61 | 40.80 | 28.72 | 33.20 | 41.85 | 33.86 | 33.10 | 38.80 |
Bayes—JW (%) | 64 | 36.50 | 52 | 29.78 | 38 | 38.01 | 36.80 | 38.12 | 39.20 |
Bayes—H (%) | 4 | 7.93 | 2.40 | 3.72 | 2 | 38.01 | 36 | 36.98 | 36.80 |
Bayes—LCS (%) | 36 | 6.34 | 6.40 | 2.65 | 0.4 | 34.82 | 35.46 | 36.30 | 39.60 |
Bayes—L (%) | 16 | 6.34 | 5.60 | 2.12 | 7.20 | 0.63 | 6.66 | 35.38 | 37.6 |
Bayes—NL (%) | 32 | 36.50 | 32.8 | 35.10 | 31.60 | 39.29 | 34.13 | 37.67 | 36.4 |
Bayes—QG (%) | 24 | 6.34 | 2.40 | 2.12 | 42.4 | 36.42 | 39.20 | 36.98 | 34.4 |