Table 4 Accuracy by class for neural networks generated using one dataset as the training set and the other dataset for test data.
From: Prediction of peptides observable by mass spectrometry applied at the experimental set level
Class | True positive rate | False positive rate | Precision | Recall | ROC Area |
|---|---|---|---|---|---|
Avian Bursal Dataset training set, Hodgkins Lymphoma test set | |||||
Not observed | 0.71 | 0.46 | 0.61 | 0.71 | 0.70 |
Observed | 0.54 | 0.29 | 0.66 | 0.54 | 0.70 |
Hodgkin's Lymphoma Model Dataset training set, Avian Bursa test set | |||||
Not observed | 0.81 | 0.41 | 0.81 | 0.73 | 0.73 |
Observed | 0.59 | 0.19 | 0.59 | 0.66 | 0.73 |