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Hongzhi (Steve), Chen 704bcaf6dd | 1 year ago | |
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README.md | 3 years ago | |
main.py | 1 year ago |
This DGL example implements the method proposed in the paper Learning from Labeled and Unlabeled Data with Label Propagation.
Contributor: xnuohz
The codebase is implemented in Python 3.7. For version requirement of packages, see below.
dgl 0.6.0.post1
torch 1.7.0
The DGL's built-in Cora, Pubmed and Citeseer datasets. Dataset summary:
Dataset | #Nodes | #Edges | #Feats | #Classes | #Train Nodes | #Val Nodes | #Test Nodes |
---|---|---|---|---|---|---|---|
Citeseer | 3,327 | 9,228 | 3,703 | 6 | 120 | 500 | 1000 |
Cora | 2,708 | 10,556 | 1,433 | 7 | 140 | 500 | 1000 |
Pubmed | 19,717 | 88,651 | 500 | 3 | 60 | 500 | 1000 |
# Cora
python main.py
# Citeseer
python main.py --dataset Citeseer --num-layers 100 --alpha 0.99
# Pubmed
python main.py --dataset Pubmed --num-layers 60 --alpha 1
Dataset | Cora | Citeseer | Pubmed |
---|---|---|---|
Results(DGL) | 69.20 | 51.30 | 71.40 |
No Description
Python C++ Jupyter Notebook Cuda Text other
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