Ranking-based evaluation of the predictive performance of different multi-label classifiers
| . | One error . | Coverage . | Average Precision . |
|---|---|---|---|
| MLCDForest | 0.1503 | 12.5520 | 0.8024 |
| DBPNN | 0.2052 | 15.4786 | 0.7249 |
| RAkEL [36] | 0.2865 | 14.2869 | 0.7382 |
| MLkNN [36] | 0.1075 | 11.5804 | 0.8155 |
| BR [36] | 0.2959 | 14.5713 | 0.7274 |
| BPMLL [36] | 0.1034 | 12.5604 | 0.7867 |
| . | One error . | Coverage . | Average Precision . |
|---|---|---|---|
| MLCDForest | 0.1503 | 12.5520 | 0.8024 |
| DBPNN | 0.2052 | 15.4786 | 0.7249 |
| RAkEL [36] | 0.2865 | 14.2869 | 0.7382 |
| MLkNN [36] | 0.1075 | 11.5804 | 0.8155 |
| BR [36] | 0.2959 | 14.5713 | 0.7274 |
| BPMLL [36] | 0.1034 | 12.5604 | 0.7867 |
Ranking-based evaluation of the predictive performance of different multi-label classifiers
| . | One error . | Coverage . | Average Precision . |
|---|---|---|---|
| MLCDForest | 0.1503 | 12.5520 | 0.8024 |
| DBPNN | 0.2052 | 15.4786 | 0.7249 |
| RAkEL [36] | 0.2865 | 14.2869 | 0.7382 |
| MLkNN [36] | 0.1075 | 11.5804 | 0.8155 |
| BR [36] | 0.2959 | 14.5713 | 0.7274 |
| BPMLL [36] | 0.1034 | 12.5604 | 0.7867 |
| . | One error . | Coverage . | Average Precision . |
|---|---|---|---|
| MLCDForest | 0.1503 | 12.5520 | 0.8024 |
| DBPNN | 0.2052 | 15.4786 | 0.7249 |
| RAkEL [36] | 0.2865 | 14.2869 | 0.7382 |
| MLkNN [36] | 0.1075 | 11.5804 | 0.8155 |
| BR [36] | 0.2959 | 14.5713 | 0.7274 |
| BPMLL [36] | 0.1034 | 12.5604 | 0.7867 |
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