> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/sdgm/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/sdgm/_mcp/server.

# Baselines

## Baseline Evaluation Metrics

On your **training job’s evaluation page**, Kumo compares your model against heuristic baselines for temporal binary classification, link prediction, and regression tasks.
These baselines show how much your model improves over simple heuristic-based approaches.

Kumo computes baselines at the per-entity level:

* **Regression tasks** use past labels as forecasts.
* **Link prediction tasks** recommend past user behavior as future predictions.

![Baseline evaluation metrics panel comparing model performance against heuristic baselines](https://fdr-prod-docs-files-public.s3.us-east-1.amazonaws.com/nvidia-sdgm.docs.buildwithfern.com/327cf22b3ea6517dbfa8b9d7d0a29f318dcffb4a95af8e8b2b0fbf05bffad379/images/Screenshot2025-06-27at10.53.33AM.png?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA6KXJSKKNFOCF7G4B%2F20260912%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20260912T192829Z&X-Amz-Expires=604800&X-Amz-Signature=296af67779c21d54184123fffc1865598eae203ae240ce05bea9054bfb23ffa8&X-Amz-SignedHeaders=host&x-amz-checksum-mode=ENABLED&x-id=GetObject)

Kumo does not support baselines when `timeframe_step` is `None`.

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## Baselines Per Task Type

The following table describes the baselines Kumo supports, organized by prediction task type:

| Task Type             | Baseline                                                                                                                                                                                                                               |
| --------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Link Prediction       | **Per Entity Frequency** - Predicts each entity using the most popular ranked list of target values from all previous splits.                                                                                                          |
| Regression            | **Per Entity Mean (Personalized Average)** - Predicts each entity using the average of all past target values from previous splits. **Per Entity Last Label** - Predicts each entity using the most recent past value as the forecast. |
| Binary Classification | **Per Entity Mean** - Predicts each entity using the average of all target values from previous splits. **Per Entity Last Label** - Predicts each entity using the previous time frame’s label.                                        |

### Why Use Baselines?

Baselines provide a reference point for measuring how much your Kumo model improves over simple heuristics.
A well-performing model should outperform these baselines significantly.