Back to Glossary
Bias
Fundamentals
Systematic deviation in data or model behavior.
Bias refers to systematic errors that lead to unfair or inaccurate results.
- Sources: Unbalanced data, sampling artifacts, faulty labels, model assumptions.
- Consequences: Group disadvantages, poor generalization.
- Mitigation: Data audits, fairness metrics, rebalancing, explainable models.