gaahinhe / dgraph_experiments

Testing a repository contaning baseline code for DGraphFin Dataset

This repo provides a collection of baselines for DGraphFin dataset. Please download the dataset from the DGraph web and place it under the folder './dataset/DGraphFin/raw'.

Environments

Implementing environment:

• numpy = 1.21.2

• pytorch = 1.6.0

• torch_geometric = 1.7.2

• torch_scatter = 2.0.8

• torch_sparse = 0.6.9

• GPU: Tesla V100 32G

Training

• TGAT

python run_tgat.py

• RGCN

python gnn.py --model rgcn --dataset DGraphFin --epochs 400 --runs 10 --device 1 --MV_trick=‘null’ --BN_trick='hetro' --BN_ratio 1.0

• MLP

python gnn.py --model mlp --dataset DGraphFin --epochs 200 --runs 10 --device 0

• GCN

python gnn.py --model gcn --dataset DGraphFin --epochs 200 --runs 10 --device 0

• GraphSAGE

python gnn.py --model sage --dataset DGraphFin --epochs 200 --runs 10 --device 0

• GraphSAGE (NeighborSampler)

python gnn_mini_batch.py --model sage_neighsampler --dataset DGraphFin --epochs 200 --runs 10 --device 0

• GAT (NeighborSampler)

python gnn_mini_batch.py --model gat_neighsampler --dataset DGraphFin --epochs 200 --runs 10 --device 0

• GATv2 (NeighborSampler)

python gnn_mini_batch.py --model gatv2_neighsampler --dataset DGraphFin --epochs 200 --runs 10 --device 0

Results:

Performance on DGraphFin(10 runs):

Methods	Train AUC	Valid AUC	Test AUC
MLP	0.7221 ± 0.0014	0.7135 ± 0.0010	0.7192 ± 0.0009
GCN	0.7108 ± 0.0027	0.7078 ± 0.0027	0.7078 ± 0.0023
GraphSAGE	0.7682 ± 0.0014	0.7548 ± 0.0013	0.7621 ± 0.0017
GraphSAGE (NeighborSampler)	0.7845 ± 0.0013	0.7674 ± 0.0005	0.7761 ± 0.0018
GAT (NeighborSampler)	0.7396 ± 0.0018	0.7233 ± 0.0012	0.7333 ± 0.0024
GATv2 (NeighborSampler)	0.7698 ± 0.0083	0.7526 ± 0.0089	0.7624 ± 0.0081