Chapter 3. Evaluate AutoML results

Procedure

1. In the OpenShift AI dashboard, click Develop and train > AutoML.
2. Click the name of your completed run to view the results.

3. Review the leaderboard, which ranks trained models by the optimized metric for your task type.

   The top-ranked model is highlighted. Click a column header to sort by a different metric.

4. To view detailed information about a model, click View details from the actions menu.

   The model details view includes evaluation metrics, feature importance scores, and a confusion matrix. Feature importance is not available for time series forecasting tasks. The confusion matrix is available for binary and multiclass classification tasks only.

5. Review the feature importance and the confusion matrix across models to verify that the best-scoring model produces predictions that you can explain and trust.
6. To register the selected model to a model registry, select Register model from the actions menu and select a model registry.
7. To save a notebook, select Save notebook from the actions menu.