Baseline Evaluation Metrics
On your training job’s evaluation page, Kumo provides comparisons of your model versus heuristic baselines for temporal binary classification, link prediction, and regression tasks. These baselines allow you to compare the results of your Kumo model against simple heuristic-based approaches.
Baselines are computed on a per-entity level, meaning:
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Regression tasks use past labels as forecasts.
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Link prediction tasks recommend past user behavior as future predictions.
Baselines are not supported when timeframe_step is None.
Baselines Per Task Type
The following table outlines current baselines supported by Kumo, organized by prediction task type:
Why Use Baselines?
Baseline models provide a reference point to determine how much your Kumo-trained model improves over simple heuristics. A well-performing model should outperform these baselines significantly.