Partial Multi-Label Learning on Image (Average Precision)
82Average PrecisionPML-MA
Evaluation results
| Method | Links | |
|---|---|---|
| PML-MAavg.#CLs=22026.04 | 82 | |
| PML-PLRavg.#CLs=22026.04 | 81 | |
| PML-NDavg.#CLs=22026.04 | 80.5 | |
| PAMBavg.#CLs=22026.04 | 79.8 | |
| PML-MAavg.#CLs=32026.04 | 79.5 | |
| FBD-PMLavg.#CLs=22026.04 | 79 | |
| P-LENFNavg.#CLs=22026.04 | 78 | |
| PML-PLRavg.#CLs=32026.04 | 77 | |
| PML-NIavg.#CLs=22026.04 | 77 | |
| PML-NDavg.#CLs=32026.04 | 76.5 | |
| FBD-PMLavg.#CLs=32026.04 | 75.5 | |
| PAMBavg.#CLs=32026.04 | 74.8 | |
| P-LENFNavg.#CLs=32026.04 | 74.7 | |
| PARTICLEavg.#CLs=22026.04 | 74.3 | |
| PML-NIavg.#CLs=32026.04 | 73.2 | |
| PML-MAavg.#CLs=42026.04 | 73 | |
| PARTICLEavg.#CLs=32026.04 | 72.5 | |
| PML-PLRavg.#CLs=42026.04 | 72 | |
| PML-NDavg.#CLs=42026.04 | 71.5 | |
| PAMBavg.#CLs=42026.04 | 71.1 | |
| FBD-PMLavg.#CLs=42026.04 | 70 | |
| PML-fpavg.#CLs=32026.04 | 68.8 | |
| PML-fpavg.#CLs=22026.04 | 67.2 | |
| P-LENFNavg.#CLs=42026.04 | 67.1 | |
| PARTICLEavg.#CLs=42026.04 | 66.8 | |
| PML-NIavg.#CLs=42026.04 | 65.3 | |
| PML-fpavg.#CLs=42026.04 | 57.3 | |
| WSC-PMLAvg#CLS=22026.04 | 0.814 | |
| PAMBAvg#CLS=22026.04 | 0.798 | |
| WSC-PMLAvg#CLS=32026.04 | 0.792 | |
| PML-LENFNAvg#CLS=22026.04 | 0.78 | |
| FBD-PMLAvg#CLS=22026.04 | 0.775 | |
| NLRAvg#CLS=22026.04 | 0.772 | |
| PML-NIAvg#CLS=22026.04 | 0.77 | |
| WSC-PMLAvg#CLS=42026.04 | 0.754 | |
| PAMBAvg#CLS=32026.04 | 0.748 | |
| PML-LENFNAvg#CLS=32026.04 | 0.747 | |
| FBD-PMLAvg#CLS=32026.04 | 0.743 | |
| PML-NIAvg#CLS=32026.04 | 0.732 | |
| NLRAvg#CLS=32026.04 | 0.724 | |
| PAMBAvg#CLS=42026.04 | 0.711 | |
| PML-fpAvg#CLS=32026.04 | 0.688 | |
| PML-fpAvg#CLS=22026.04 | 0.672 | |
| PML-LENFNAvg#CLS=42026.04 | 0.671 | |
| FBD-PMLAvg#CLS=42026.04 | 0.669 | |
| PML-NIAvg#CLS=42026.04 | 0.653 | |
| NLRAvg#CLS=42026.04 | 0.648 | |
| PML-fpAvg#CLS=42026.04 | 0.573 |