Average odds difference metric
Last updated: Feb 13, 2025
The average odds difference metric measures the difference in false positive and false negative rates between monitored and reference groups.
Metric details
Average odds difference is a fairnes evaluation metric that can help determine whether your asset produces biased outcomes.
Scope
The average odds difference metric evaluates generative AI assets and machine learning models.
- Types of AI assets:
- Prompt templates
- Machine learning models
- Generative AI tasks: Text classification
- Machine learning problem type: Binary classification
Scores and values
The average odds difference metric score indicates the difference in false positive and false negative rates for monitored and reference groups.
- Range of values: 0.0-1.0
- Best possible score: 0.0
- Ratios:
- At 0: Both groups have equal odds
- Under 0: Biased outcomes for monitored group
- Over 0: Biased outcomes for reference group
Do the math
The following formula is used for calculating false positive rate (FPR):
The following formula is used for calculating true positive rate (TPR):
The following formula is used for calculating average odds difference:
Parent topic: Evaluation metrics
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