Azure machine learning AutoMl

Question

Hi dear microsoft support team, I am learning to use Azure machine learning and today I used Automated ML on machine learning studio. The tutorial from microsoft course said that I can set an exit criteria for my regression model so it stops when it meet the condition. But as much as I search I can not find where can I implement the exit criterion when I am configuring Automated ML job on machine learning studio. I would be happy if you help me with this. Best regards, moein sahraei

Answer 1

Hi @Moein Sahraei@Moein Sahraei

Thank you for using the Microsoft Q&A forum.

To set the exit criterion for your regression model in Automated ML, you can set job training settings and exit criteria with the training and limits settings. For example, you can set the "Max trials," "Max nodes," "Experiment timeout," and "Iteration timeout" parameters to control the duration and resources used by your Automated ML job. Additionally, you can set the "Metric score threshold" parameter to specify the minimum metric score for all pipelines. This ensures that if you have a defined target metric you want to reach, you do not spend more time on the training job than necessary. Please see below screen.

You can find more information about configuring your Automated ML experiment settings and exit criteria in the Azure documentation.

how-to-configure-auto-train-experiment-settings.

exit-criteria-how-to-configure.

early-termination-policies.

Hope this helps.

---

If this answers your query, do click Accept Answer and Yes for was this answer helpful.