From: In-silico predictive mutagenicity model generation using supervised learning approaches
Classifiers | Data set | Accuracy% | Precision % | Recall% | ROC |
---|---|---|---|---|---|
Naïve Bayes | Set 1 | 55.76 | 54.3 | 42.78 | 57.50% |
Set 2 | 55.88 | 54.6 | 42.27 | 58.00% | |
Set 3 | 61.05 | 63.2 | 61.1 | 66.8% | |
Random Forest | Set 1 | 84.85 | 86.3 | 81 | 93.1% |
Set 2 | 87.86 | 87.7 | 86.58 | 94.30% | |
Set 3 | 90.14 | 90.1 | 90.1 | 96.8% | |
J48 | Set 1 | 80.88 | 79.0 | 80.50 | 84.20% |
Set 2 | 84.37 | 85.7 | 80.50 | 86.20% | |
Set 3 | 87.01 | 87 | 87 | 88.7% | |
SMO | Set 1 | 62.01 | 62.6 | 49.62 | 67.60% |
Set 2 | 69.23 | 71.8 | 57.97 | 68.70% | |
Set 3 | 56.12 | 57 | 56.1 | 61.2% |