From: In-silico predictive mutagenicity model generation using supervised learning approaches
Classifiers | Data set | Accuracy% | Precision % | Recall% | ROC |
---|---|---|---|---|---|
Naïve Bayes | Set 1 | 49.08 | 53.3 | 36.80 | 50.30% |
Set 2 | 49.28 | 53.7 | 36.29 | 50.60% | |
Set 3 | 49.01 | 51.5 | 49 | 55.5% | |
Random Forest | Set 1 | 64.65 | 66.4 | 64.7 | 67.3% |
Set 2 | 61.61 | 66.6 | 56.21 | 64.50% | |
Set 3 | 62.89 | 64 | 62.9 | 65.60% | |
J48 | Set 1 | 63.16 | 68.6 | 57.10 | 64.60% |
Set 2 | 60.39 | 66 | 53.04 | 62.50% | |
Set 3 | 61.27 | 62.1 | 62.3 | 60.8% | |
SMO | Set 1 | 50.57 | 55.3 | 38.57 | 55.90% |
Set 2 | 57.14 | 63.2 | 46.95 | 57.90% | |
Set 3 | 56.12 | 57 | 56.1 | 61.2% |