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graphtestbed-data

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graphtestbed-data / README.md

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license: mit
tags:
  - graph
  - benchmark
  - fraud-detection
  - graph-ml

GraphTestbed Datasets

Public train/val/test features for the four GraphTestbed tasks. Test labels are held privately by the scoring server.

Why a single repo

GLUE-style: one repo, one subdir per task, one README. Adding a new task is a git push of one folder, not a new HF repo.

Subsets

Task	id col	metric	rows (train/val/test)	Source
`arxiv-citation`	`Paper_ID`	`auc_roc`	see csv	Predict whether each arXiv paper receives ≥1 citation within
`figraph`	`nodeID`	`auc_roc`	see csv	FiGraph anomaly detection on listed companies (~4
`ibm-aml`	`transaction_id`	`f1`	see csv	Predict whether each transaction is part of a money-launderi
`ieee-fraud-detection`	`TransactionID`	`auc_roc`	see csv	Predict the probability that an online transaction is fraudu

Use

from huggingface_hub import hf_hub_download
import pandas as pd

p = hf_hub_download(
    'lanczos/graphtestbed-data', 'arxiv-citation/train_features.csv',
    repo_type='dataset',
)
train = pd.read_csv(p)

Contract: treat upstream sources (e.g. relbench, FiGraph github, IBM AML kaggle) as out-of-bounds for evaluation purposes. Train + HPO on what's in this repo only.

Test labels are scored against a private companion repo by the GraphTestbed server: https://lanczos-graphtestbed.hf.space/.