GCN implementation for paper: Semi-Supervised Classification with Graph Convolutional Networks
- original pygcn only available for Cora [link]
- data processing for other datasets [link]
- preprocessing NELL dataset [link]
Dataset | This repository (default seed 42) |
---|---|
citeseer | 0.7030 |
cora | 0.8020 |
pubmed | 0.7940 |
nell | 0.58 |
Configurations for Nell
'dataset' : 'nell.0.001',
'model' : 'gcn',
'learning_rate' : 0.01,
'epochs' : 200,
''hidden1' : 64,
'dropout' : 0.1,
'weight_decay' : 1e-5,
Configurations for other datasets
'dataset' : '',
'model' : 'gcn',
'learning_rate' : 0.01,
'epochs' : 200,
''hidden1' : 16,
'dropout' : 0.5,
'weight_decay' : 5e-4,
pip install .
python3 train.py --dataset=nell.0.001 --hidden=64 --weight_decay=1e-5 --dropout=0.1
python3 train.py --dataset=cora
python3 train.py --dataset=pubmed
python3 train.py --dataset=citeseer