Partial Multi-Label Learning on corel5k
0.173Ranking LossPML-fp
Evaluation results
| Method | Links | ||
|---|---|---|---|
| PML-fpAvg#CLS=72026.04 | 0.173 | — | |
| PML-fpAvg#CLS=92026.04 | 0.18 | — | |
| PML-fpAvg#CLS=112026.04 | 0.181 | — | |
| WSC-PMLAvg#CLS=72026.04 | 0.184 | — | |
| WSC-PMLAvg#CLS=92026.04 | 0.192 | — | |
| WSC-PMLAvg#CLS=112026.04 | 0.197 | — | |
| PML-NIAvg#CLS=72026.04 | 0.215 | — | |
| PML-LENFNAvg#CLS=72026.04 | 0.217 | — | |
| FBD-PMLAvg#CLS=72026.04 | 0.221 | — | |
| PAMBAvg#CLS=72026.04 | 0.222 | — | |
| PML-NIAvg#CLS=92026.04 | 0.223 | — | |
| PML-LENFNAvg#CLS=92026.04 | 0.224 | — | |
| FBD-PMLAvg#CLS=92026.04 | 0.227 | — | |
| PAMBAvg#CLS=92026.04 | 0.229 | — | |
| PML-NIAvg#CLS=112026.04 | 0.229 | — | |
| PML-LENFNAvg#CLS=112026.04 | 0.23 | — | |
| FBD-PMLAvg#CLS=112026.04 | 0.232 | — | |
| PAMBAvg#CLS=112026.04 | 0.235 | — | |
| NLRAvg#CLS=72026.04 | 0.241 | — | |
| NLRAvg#CLS=92026.04 | 0.246 | — | |
| NLRAvg#CLS=112026.04 | 0.249 | — | |
| FBD-PMLAvg#CLS=72026.04 | — | 27.6 | |
| FBD-PMLAvg#CLS=92026.04 | — | 26.9 | |
| FBD-PMLAvg#CLS=112026.04 | — | 26.3 | |
| NLRAvg#CLS=72026.04 | — | 27.5 | |
| NLRAvg#CLS=92026.04 | — | 27.3 | |
| NLRAvg#CLS=112026.04 | — | 27 | |
| PAMBAvg#CLS=72026.04 | — | 24 | |
| PAMBAvg#CLS=92026.04 | — | 22.9 | |
| PAMBAvg#CLS=112026.04 | — | 22.7 | |
| PML-fpAvg#CLS=72026.04 | — | 28.4 | |
| PML-fpAvg#CLS=92026.04 | — | 20.1 | |
| PML-fpAvg#CLS=112026.04 | — | 20.1 | |
| PML-LENFNAvg#CLS=72026.04 | — | 27.9 | |
| PML-LENFNAvg#CLS=92026.04 | — | 27.1 | |
| PML-LENFNAvg#CLS=112026.04 | — | 26.4 | |
| PML-NIAvg#CLS=72026.04 | — | 28 | |
| PML-NIAvg#CLS=92026.04 | — | 27.3 | |
| PML-NIAvg#CLS=112026.04 | — | 26.5 | |
| WSC-PMLAvg#CLS=72026.04 | — | 30.6 | |
| WSC-PMLAvg#CLS=92026.04 | — | 30.1 | |
| WSC-PMLAvg#CLS=112026.04 | — | 29.5 |