Extreme Multi-label Classification on AmazonCat-13K legacy (test)
0.969Precision@1CascadeXML
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| CascadeXMLfeatures=DNN, ensemble_size=3 models, input_sequence_length=2562022.10 | 0.969 | 0.8413 | 0.6878 | |
| XR-Transformerfeatures=DNN + tf-idf, ensemble_size=3 models, input_sequence_length=2562022.10 | 0.9679 | 0.8366 | 0.6804 | |
| LightXMLfeatures=DNN, ensemble_size=3 models, input_sequence_length=2562022.10 | 0.9677 | 0.8398 | 0.6863 | |
| CascadeXMLfeatures=DNN + tf-idf, ensemble_size=3 models, input_sequence_length=2562022.10 | 0.9671 | 0.8407 | 0.6869 | |
| X-Transformerfeatures=DNN + tf-idf, ensemble_size=9 models, input_sequence_length=2562022.10 | 0.9648 | 0.8341 | 0.6819 | |
| AttentionXMLfeatures=DNN, ensemble_size=3 models, input_sequence_length=2562022.10 | 0.9584 | 0.8239 | 0.6732 | |
| XR-Linear2022.10 | 0.9464 | 0.7998 | 0.6479 | |
| DISMEC2022.10 | 0.9381 | 0.7908 | 0.6406 | |
| Parabel2022.10 | 0.9302 | 0.7914 | 0.6451 | |
| Bonsai2022.10 | 0.9298 | 0.7913 | 0.6446 | |
| eXtremeText2022.10 | 0.925 | 0.7812 | 0.6351 |