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Mufei Li be444e52d9 [Doc/Feature] Refactor, doc update and behavior fix for graphs (#1983)
* Update graph

* Fix for dgl.graph

* from_scipy

* Replace canonical_etypes with relations

* from_networkx

* Update for hetero_from_relations

* Roll back the change of canonical_etypes to relations

* heterograph

* bipartite

* Update doc

* Fix lint

* Fix lint

* Fix test cases

* Fix

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* Update

* Fix test

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* Use DGLError

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* rewrite sanity checks

* delete unnecessary checks

* Update

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Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
Co-authored-by: Quan Gan <coin2028@hotmail.com>
2020-08-18 04:26:29 +08:00

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Markdown

# Relational-GCN
* Paper: [https://arxiv.org/abs/1703.06103](https://arxiv.org/abs/1703.06103)
* Author's code for entity classification: [https://github.com/tkipf/relational-gcn](https://github.com/tkipf/relational-gcn)
* Author's code for link prediction: [https://github.com/MichSchli/RelationPrediction](https://github.com/MichSchli/RelationPrediction)
### Dependencies
* Tensorflow 2.2+
* requests
* rdflib
* pandas
```
pip install requests tensorflow rdflib pandas
export DGLBACKEND=tensorflow
```
Example code was tested with rdflib 4.2.2 and pandas 0.23.4
### Entity Classification
AIFB: accuracy 92.78% (5 runs, DGL), 95.83% (paper)
```
python3 entity_classify.py -d aifb --testing --gpu 0
```
MUTAG: accuracy 71.47% (5 runs, DGL), 73.23% (paper)
```
python3 entity_classify.py -d mutag --l2norm 5e-4 --n-bases 30 --testing --gpu 0
```
BGS: accuracy 93.10% (5 runs, DGL n-base=25), 83.10% (paper n-base=40)
```
python3 entity_classify.py -d bgs --l2norm 5e-4 --n-bases 25 --testing --gpu 0
```