# Fairness Metrics¶

Supported metrics for model fairness checks are configurable. You can change the metrics for the selected project and/or model in **Project Settings** (pictured next) after signing in at app.truera.net.

TruEra supports a wide variety of fairness metrics for both classification and regression models. Selecting the appropriate root cause analyses to understand the sources of bias is discussed under **Exploring TruEra Diagnostics** in Fairness.

Note

Measurements are labeled ** TP** (true positive),

**(false positive),**

`FP`

**(true negative), and**

`TP`

**(false negative).**

`FN`

## Classification models¶

Name | Range | Notes |
---|---|---|

Disparate impact ratio | [0, +inf) | Ratio of proportion predicted to be the `y=1` class (i.e. `(TP + FP) / (TP + FP + TN + FN)` ). |

Statistical parity difference | [-1, 1] | Difference of proportion predicted to be the `y=1` class (i.e. `(TP + FP) / (TP + FP + TN + FN)` ). |

True positive rate ratio | [0, +inf) | Ratio of true positive rates: `TP / (TP + FN)` . |

True positive rate difference | [-1, 1] | Difference of true positive rates: `TP / (TP + FN)` . |

False positive rate ratio | [0, +inf) | Ratio of false positive rates: `FP / (FP + TN)` . |

False positive rate difference | [-1, 1] | Difference of false positive rates: `FP / (FP + TN)` . |

True negative rate ratio | [0, +inf) | Ratio of true negative rates: `TN / (FP + TN)` . |

True negative rate difference | [-1, 1] | Difference of true negative rates: `TN / (FP + TN)` . |

False negative rate ratio | [0, +inf) | Ratio of false negative rates: `FN / (TP + FN)` . |

False negative rate difference | [-1, 1] | Difference of false negative rates: `FN / (TP + FN)` . |

Equality of opportunity ratio | [0, +inf) | Equivalent to true positive rate ratio when the `y=1` class is favorable and true negative ratio otherwise. |

Equality of opportunity difference | [-1, 1] | Equivalent to true positive rate difference when the `y=1` class is favorable and true negative difference otherwise. |

Predictive parity ratio | [0, +inf) | Ratio of predictive parity: `TP / (TP + FP)` . Also referred to as "acceptance rate ratio". |

Predictive parity difference | [-1, 1] | Difference of predictive parity: `TP / (TP + FP)` . Also referred to as "acceptance rate difference". |

Treatment equality difference | (-inf, +inf) | Difference of ratio of false positive rate to false negative rate. |

Conditional acceptance difference | (-inf, +inf) | Difference of conditional acceptance: `(TP + FN) / (TP + FP)` . |

Conditional rejection difference | (-inf, +inf) | Difference of conditional rejection: `(TN + FP) / (TN + FN)` . |

Average odds difference | [-1, 1] | Difference of average of true positive rate and false positive rate. |

### Choosing a fairness metric for classification models¶

## Regression Models¶

Name | Range | Notes |
---|---|---|

Mean score difference | (-inf, +inf) | Difference in average model score. |

L1 error difference | (-inf, +inf) | Difference in average L1 error (i.e. mean absolute error). |

L2 error difference | (-inf, +inf) | Difference in average L2 error (i.e. mean squared error). |

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