# Evaluating AI models with Watson OpenScale #

IBM Watson OpenScale tracks and measures outcomes from your AI models, and helps ensure that they remain fair, explainable, and compliant no matter where your models were built or are running\. Watson OpenScale also detects and helps correct the drift in accuracy when an AI model is in production\.

**Required service** : Watson Machine Learning

**Training data format** : Relational: Tables in relational data sources : Tabular: Excel files (\.xls or \.xlsx), CSV files : Textual: In the supported relational tables or files

**Connected data** : Cloud Object Storage (infrastructure) : Db2

**Data size** : Any

Enterprises use model evaluation as part of an AI governance strategy to make sure that models in development and production meet established compliance standards\. This approach ensures that AI models are free from bias, can be easily explained and understood by business users, and are auditable in business transactions\. You can evaluate models regardless of the tools and frameworks that you use to build and run models\.

Watch this short video to learn more about Watson OpenScale:

This video provides a visual method to learn the concepts and tasks in this documentation\.

### Trustworthy AI in action ###

To learn more about model evaluation in action, see [How AI picks the highlights from Wimbledon fairly and fast](https://www.ibm.com/blog/how-ai-picks-the-highlights-from-wimbledon-fairly-and-fast/)\.

## Components of Watson OpenScale ##

Watson OpenScale has four main areas:

<!-- <ul> -->

 *  **Insights:** The Insights page displays the models that you are monitoring and provides status on the results of model evaluations\.
 *  **Explain a transaction:** The Explanations page describes how the model determined a prediction\. You can understand and be confident in the model by viewing some of the most important factors that led to its predictions\.
 *  **Configuration:** The Configuration page can be used to select a database, set up a machine learning provider, and optionally add integrated services\.
 *  **Support:** The Support page provides you with resources to get the help you need with Watson OpenScale\. Access product documentation or connect with IBM Community on Stack Overflow\. To create a service ticket with the IBM Support team, click **Manage tickets**\.

<!-- </ul> -->

### Evaluations ###

Evaluations validate your deployments against specified metrics\. Configure alerts that indicate when a threshold is crossed for a metric\. Watson OpenScale evaluates your deployments based on three default monitors:

<!-- <ul> -->

 *  **Quality** describes the model’s ability to provide correct outcomes based on labeled test data called Feedback data\.
 *  **Fairness** describes how evenly the model delivers favorable outcomes between groups\. The Fairness monitor looks for biased outcomes in your model\.
 *  **Drift** warns you of a drop in accuracy or data consistency\.

<!-- </ul> -->

Note:You can also create **Custom** evaluations for your deployment\.

## Next steps ##

## Learn more ##

**Parent topic:**[Managing predictive deployments](https://dataplatform.cloud.ibm.com/docs/content/wsj/wmls/wmls-deploy-overview.html)

<!-- </article "role="article" "> -->