Classifier
| Accuracy1 | False Pos. Rate2 | False Neg. Rate3 |
---|
J48 | 99.28% | 37.7% | 0.183% |
NaïveBayes | 97.82% | 12.2% | 2.04% |
NaïveBayes (-K) 4 | 99.24% | 44.5% | 0.127% |
Random Forest | 99.20% | 45.9% | 0.149% |
UMD Overlapper | 74.90% | 76.5% | 23.3% |
- 1Accuracy is defined as the number of true positive and true negative overlaps divided by the total number of overlaps
- 2The false positive rate is defined as the number of false positive overlaps divided by the number of false overlaps
- 3The false negative rate is defined as the number of false negative overlaps divided by the number of true overlaps
- 4NaïveBayes with kernel estimation