We are loading the service guidance for this workflow.
We are loading the dataset structure and key columns for this workflow.
Check the file for missing information, unsuitable columns, and other issues that may affect the results.
Resolve blocking issues, review warnings, then choose models and start training.
Query-aware rankers are preselected; pairwise, listwise, and pointwise variants remain available for targeted comparisons.
These baselines learn relevance scores first, then evaluate ranked order within held-out query groups.
Your recommended setup appears after the data check is complete.
AutoML will compare a practical mix of suitable models. Change it only when you have a specific reason.
Your estimate appears after you choose a setup.