# SupervisedAnomalyDetector

A supervised anomaly detector.

## Methods

> [!NOTE]
>
> **learn\_one**
>
> Update the model.
>
> **Parameters**
>
> - **x** — `dict[base.typing.FeatureName, Any]`
> - **y** — `base.typing.Target`

> [!NOTE]
>
> **score\_one**
>
> Return an outlier score.
>
> A high score is indicative of an anomaly. A low score corresponds a normal observation.
>
> **Parameters**
>
> - **x** — `dict[base.typing.FeatureName, Any]`
> - **y** — `base.typing.Target`
>
> **Returns**
>
> `float`: An anomaly score. A high score is indicative of an anomaly. A low score corresponds a