# Model evaluation and metrics

> Model evaluation and metrics - Model evaluation and metrics accelerators that you can add to your
> experiment workflow.

This Markdown file sits beside the HTML page at the same path (with a `.md` suffix). It summarizes the topic and lists links for tools and LLM context.

Companion generated at `2026-05-06T18:17:09.583402+00:00` (UTC).

## Primary page

- [Model evaluation and metrics](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/model-eval-metrics/index.html): Full documentation for this topic (HTML).

## Related documentation

- [Developer documentation](https://docs.datarobot.com/en/docs/api/index.html): Linked from this page.
- [Developer learning](https://docs.datarobot.com/en/docs/api/dev-learning/index.html): Linked from this page.
- [AI accelerators](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/index.html): Linked from this page.
- [Custom metrics for model selection](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/model-eval-metrics/ai-custom-metrics.html): Linked from this page.
- [t-SNE dimensionality reduction](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/model-eval-metrics/dim-reduction.html): Linked from this page.
- [Monitor generative AI metrics](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/model-eval-metrics/genai-metrics.html): Linked from this page.
- [Event log viewer](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/model-eval-metrics/log-viewer.html): Linked from this page.
- [LLM observability](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/model-eval-metrics/observability.html): Linked from this page.
- [Partial dependence plots (PDP/ICE)](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/model-eval-metrics/pdp-ice.html): Linked from this page.
- [LIME explanations for models](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/model-eval-metrics/run-lime.html): Linked from this page.
- [Steel defect detection](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/model-eval-metrics/steel-plate.html): Linked from this page.
- [Export model insights](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/model-eval-metrics/viz-output.html): Linked from this page.

## Documentation content

| Topic | Description |
| --- | --- |
| Custom metrics for model selection | Demonstrates how to leverage DataRobot's Python client to extract predictions, compute custom metrics, and sort DataRobot models accordingly. |
| t-SNE dimensionality reduction | Learn how to use t-SNE for dimensionality reduction and visualization of high-dimensional data, with examples for exporting these insights as files and plots. |
| Monitor generative AI metrics | Monitor LLMs and generative AI solutions to measure alignment, return on investment, and provide guardrails using custom metrics. |
| Event log viewer | Change the output of the User Activity Monitor to drop or anonymize columns for privacy while maintaining reporting consistency. |
| LLM observability | Enable LLMOps or Observability in your existing Generative AI Solutions without refactoring code, with examples for major LLMs. |
| Partial dependence plots (PDP/ICE) | Create one-way and two-way partial dependence plots (PDP), and Individual Conditional Expectations (ICE) insights using DataRobot. |
| LIME explanations for models | Apply Local Interpretable Model-agnostic Explanations (LIME) to models built and deployed with DataRobot. |
| Steel defect detection | Train a highly accurate and robust machine learning model capable of detecting and classifying any-sized scratch present in steel plates. |
| Export model insights | Review examples for exporting a variety of DataRobot model insights and performance metrics as both machine-readable files and plots in multiple formats. |