# Bias Drift Violations


Bias drift jobs evaluate the baseline constraints provided by the [baseline configuration](https://docs.amazonaws.cn/sagemaker/latest/APIReference/API_CreateModelBiasJobDefinition.html#sagemaker-CreateModelBiasJobDefinition-request-ModelBiasBaselineConfig) against the analysis results of current `MonitoringExecution`. If violations are detected, the job lists them to the *constraint\$1violations.json* file in the execution output location, and marks the execution status as [Interpret results](model-monitor-interpreting-results.md).

Here is the schema of the bias drift violations file.
+ `facet` – The name of the facet, provided by the monitoring job analysis configuration facet `name_or_index`. 
+ `facet_value` – The value of the facet, provided by the monitoring job analysis configuration facet `value_or_threshold`.
+ `metric_name` – The short name of the bias metric. For example, "CI" for class imbalance. See [Pre-training Bias Metrics](clarify-measure-data-bias.md) for the short names of each of the pre-training bias metrics and [Post-training Data and Model Bias Metrics](clarify-measure-post-training-bias.md) for the short names of each of the post-training bias metrics.
+ `constraint_check_type` – The type of violation monitored. Currently only `bias_drift_check` is supported.
+ `description` – A descriptive message to explain the violation.

```
{
    "version": "1.0",
    "violations": [{
        "facet": "string",
        "facet_value": "string",
        "metric_name": "string",
        "constraint_check_type": "string",
        "description": "string"
    }]
}
```

A bias metric is used to measure the level of equality in a distribution. A value close to zero indicates that the distribution is more balanced. If the value of a bias metric in the job analysis results file (analysis.json) is worse than its corresponding value in the baseline constraints file, a violation is logged. As an example, if the baseline constraint for the DPPL bias metric is `0.2`, and the analysis result is `0.1`, no violation is logged because `0.1` is closer to `0` than `0.2`. However, if the analysis result is `-0.3`, a violation is logged because it is farther from `0` than the baseline constraint of `0.2`.

```
{
    "version": "1.0",
    "violations": [{
        "facet": "Age",
        "facet_value": "40",
        "metric_name": "CI",
        "constraint_check_type": "bias_drift_check",
        "description": "Value 0.0751544567666083 does not meet the constraint requirement"
    }, {
        "facet": "Age",
        "facet_value": "40",
        "metric_name": "DPPL",
        "constraint_check_type": "bias_drift_check",
        "description": "Value -0.0791244970125596 does not meet the constraint requirement"
    }]
}
```