A new agent-based simulation generates synthetic loan data with controllable bias, and experiments show how different fairness fixes trade off accuracy against equality.
Annual Review of political science 17(1), 1–20 (2014) 14 Ricardo Inácio, Zafeiris Kokkinogenis, Vitor Cerqueira, and Carlos Soares
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ML 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Simulating Biases for Interpretable Fairness in Offline and Online Classifiers
A new agent-based simulation generates synthetic loan data with controllable bias, and experiments show how different fairness fixes trade off accuracy against equality.