> For the complete documentation index, see [llms.txt](https://docs.geopard.tech/geopard-tutorials/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.geopard.tech/geopard-tutorials/esp/tour-del-producto-aplicacion-web/geopard-mcp/limpiar-y-calibrar-datos-de-rendimiento.md).

# Limpiar y calibrar datos de rendimiento

Aprende a garantizar una limpieza y calibración estadísticamente sólidas de tus conjuntos de datos de rendimiento usando un LLM con GeoPard MCP.

En este caso de uso, trabajamos con conjuntos de datos de rendimiento para comprender la distribución y la calidad de los datos cosechados en todo el lote. Usando el GeoPard MCP conectado, un LLM recupera resúmenes estadísticos del conjunto de datos de rendimiento original, detecta irregularidades o ruido de los sensores e identifica dónde se requiere limpieza o calibración.

Una vez completadas las comprobaciones de calidad, el LLM activa el flujo de trabajo de limpieza y calibración de GeoPard MCP con los parámetros óptimos.

{% hint style="success" %}
Asegúrese de que GeoPard MCP esté conectado antes de ejecutar este flujo de trabajo. Los detalles de la configuración se proporcionan [aquí](/geopard-tutorials/esp/tour-del-producto-aplicacion-web/geopard-mcp/conectar-geopard-mcp.md).
{% endhint %}

## Conjunto de datos de rendimiento individual

{% @arcade/embed url="<https://app.arcade.software/share/Zjf8Hpwf0Ykij1Dl5r4L>" flowId="Zjf8Hpwf0Ykij1Dl5r4L" %}

### Antes

<figure><img src="https://2708050521-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYICBELdyAXXebKAzfLOR%2Fuploads%2FBTboCq739Ds6EWIoN8YI%2Fimage.png?alt=media&amp;token=d7b2b51d-a67b-43c1-9a57-7e9338abc93a" alt=""><figcaption></figcaption></figure>

### Después

<figure><img src="https://2708050521-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYICBELdyAXXebKAzfLOR%2Fuploads%2FcIBWxG32gH31rkN45Cq9%2Fimage.png?alt=media&amp;token=970b3cd3-1a7c-438d-bac0-a2db73d146de" alt=""><figcaption></figcaption></figure>

## Calibración por lotes del conjunto de datos de rendimiento

{% @arcade/embed url="<https://app.arcade.software/share/bibREyFI1hqQvPk7rBFq>" flowId="bibREyFI1hqQvPk7rBFq" %}

### Antes

<figure><img src="https://2708050521-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYICBELdyAXXebKAzfLOR%2Fuploads%2FUATNQLP0u88zsnlLkAAm%2Fimage.png?alt=media&amp;token=a85329be-0cb9-4c38-88c5-8b591638edf9" alt=""><figcaption></figcaption></figure>

### Después

<figure><img src="https://2708050521-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FYICBELdyAXXebKAzfLOR%2Fuploads%2Fimu4ak8G06puVVlpSS6w%2Fimage.png?alt=media&amp;token=51ec2b97-fa4e-403a-af7c-e68506a872c7" alt=""><figcaption></figcaption></figure>


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