Node Classification On Pubmed 01
المقاييس
Accuracy
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
جدول المقارنة
| اسم النموذج | Accuracy |
|---|---|
| break-the-ceiling-stronger-multi-scale-deep | 77.21% |
| diffusion-convolutional-neural-networks | 73.1% |
| graph-attention-networks | 59.6% |
| convolutional-networks-on-graphs-for-learning | 70.3% |
| gated-graph-sequence-neural-networks | 70.4% |
| convolutional-neural-networks-on-graphs-with | 55.2% |
| lanczosnet-multi-scale-deep-graph | 73.4 ± 5.1 |
| break-the-ceiling-stronger-multi-scale-deep | 75.30% |
| view-consistent-heterogeneous-network-on | 76.8% |
| inductive-representation-learning-on-large | 65.4% |
| lanczosnet-multi-scale-deep-graph | 72.8 ± 4.6 |
| break-the-ceiling-stronger-multi-scale-deep | 74.40% |
| mutual-teaching-for-graph-convolutional | 73.1% |
| break-the-ceiling-stronger-multi-scale-deep | 73.83% |