rel-avito: user clicks (Classification)

This runner now uses the official relbench dataset loader and materializes the Avito tables locally before GraphReduce runs. The example no longer depends on the legacy S3 parquet mirror.

from relbench_avito_user_clicks import run_rel_avito_user_clicks

df, auc, n_features, materialized, target = run_rel_avito_user_clicks()
print(materialized)
print(target, auc, n_features, len(df))

Current implementation:

• examples/relbench_avito_user_clicks.py
• examples/relbench_avito_common.py

Interactive Runner

Save API URL Run rel-avito user clicks

Idle