Table 7. Labeling accuracy results obtained with 3 sources, semi-supervised and unsupervised, for A2 vs. AG (GL+ME).
| STE, Training set | STE, Test set | LTE, Training set | LTE, Test set | ||
| A2 vs. AG | Total | 89.7% (131/146) | 86.0% (43/50) | 77.5% (100/129) | 60.0% (30/50) |
| Unsupervised | A2 | 95.5% (21/22) | 100.0% (10/10) | 100.0% (20/20) | 100.0% (10/10) |
| AG | 88.7% (110/124) | 82.5% (33/40) | 73.4% (80/109) | 50.0% (20/40) | |
| BER | 0.079 | 0.088 | 0.133 | 0.250 | |
| A2 vs. AG | Total | 97.9% (143/146) | 84.0% (42/50) | 97.7% (126/129) | 66.0% (33/50) |
| Semi-supervised | A2 | 100.0% (22/22) | 100.0% (10/10) | 100.0% (20/20) | 100.0% (10/10) |
| AG | 97.6% (121/124) | 80.0% (32/40) | 97.2% (106/109) | 57.5% (23/40) | |
| BER | 0.012 | 0.100 | 0.014 | 0.213 |
Summary of the labeling accuracy obtained for the training and test set when three sources were calculated in a fully unsupervised way, and a semi-supervised way (IMA+Convex-NMF), for the discrimination problem A2 vs. AG (GL+ME) at STE and LTE. They include the accuracy (total and by tumor type); the number of correctly labeled samples from the total, in parentheses; and BER of the classification.