Table 3.
Prediction performance of the models with 80 : 20 training samples and test samples ratio as the ability to identify the positive outcome.
| %All features | %Target and reference p2p amplitude and onset latency | %Target and reference p2p amplitude, onset latency, and AUC | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| >200% method | >50% method | Fine KNN | Weighted KNN | Ensemble Bagged Trees | Ensemble Subspace KNN | SVM Fine Gaussian | Fine KNN | Weighted KNN | Ensemble Bagged Trees | Ensemble Subspace KNN | Fine KNN | Weighted KNN | Ensemble Bagged Trees | Ensemble Subspace KNN | |
| True positive | 25% | 75% | 75.00% | 100.00% | 100.00% | 87.50% | 100.00% | 100.00% | 100.00% | 100.00% | 100.00% | 87.50% | 100.00% | 87.50% | 87.50% |
| True negative | 67% | 67% | 33.33% | 0.00% | 0.00% | 0.00% | 0.00% | 33.33% | 0.00% | 0.00% | 0.00% | 33.33% | 0.00% | 0.00% | 0.00% |
| False positive | 33% | 33% | 66.67% | 100.00% | 100.00% | 100.00% | 100.00% | 66.67% | 100.00% | 100.00% | 100.00% | 66.67% | 100.00% | 100.00% | 100.00% |
| False negative | 75% | 25% | 25.00% | 0.00% | 0.00% | 12.50% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 12.50% | 0.00% | 12.50% | 12.50% |